Bug Summary

File:build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/llvm/lib/Transforms/Vectorize/LoopVectorize.cpp
Warning:line 2907, column 23
Called C++ object pointer is null

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clang -cc1 -cc1 -triple x86_64-pc-linux-gnu -analyze -disable-free -clear-ast-before-backend -disable-llvm-verifier -discard-value-names -main-file-name LoopVectorize.cpp -analyzer-store=region -analyzer-opt-analyze-nested-blocks -analyzer-checker=core -analyzer-checker=apiModeling -analyzer-checker=unix -analyzer-checker=deadcode -analyzer-checker=cplusplus -analyzer-checker=security.insecureAPI.UncheckedReturn -analyzer-checker=security.insecureAPI.getpw -analyzer-checker=security.insecureAPI.gets -analyzer-checker=security.insecureAPI.mktemp -analyzer-checker=security.insecureAPI.mkstemp -analyzer-checker=security.insecureAPI.vfork -analyzer-checker=nullability.NullPassedToNonnull -analyzer-checker=nullability.NullReturnedFromNonnull -analyzer-output plist -w -setup-static-analyzer -analyzer-config-compatibility-mode=true -mrelocation-model pic -pic-level 2 -mframe-pointer=none -fmath-errno -ffp-contract=on -fno-rounding-math -mconstructor-aliases -funwind-tables=2 -target-cpu x86-64 -tune-cpu generic -debugger-tuning=gdb -ffunction-sections -fdata-sections -fcoverage-compilation-dir=/build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/build-llvm -resource-dir /usr/lib/llvm-15/lib/clang/15.0.0 -D _DEBUG -D _GNU_SOURCE -D __STDC_CONSTANT_MACROS -D __STDC_FORMAT_MACROS -D __STDC_LIMIT_MACROS -I lib/Transforms/Vectorize -I /build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/llvm/lib/Transforms/Vectorize -I include -I /build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/llvm/include -D _FORTIFY_SOURCE=2 -D NDEBUG -U NDEBUG -internal-isystem /usr/lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10 -internal-isystem /usr/lib/gcc/x86_64-linux-gnu/10/../../../../include/x86_64-linux-gnu/c++/10 -internal-isystem /usr/lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/backward -internal-isystem /usr/lib/llvm-15/lib/clang/15.0.0/include -internal-isystem /usr/local/include -internal-isystem /usr/lib/gcc/x86_64-linux-gnu/10/../../../../x86_64-linux-gnu/include -internal-externc-isystem /usr/include/x86_64-linux-gnu -internal-externc-isystem /include -internal-externc-isystem /usr/include -fmacro-prefix-map=/build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/build-llvm=build-llvm -fmacro-prefix-map=/build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/= -fcoverage-prefix-map=/build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/build-llvm=build-llvm -fcoverage-prefix-map=/build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/= -O3 -Wno-unused-command-line-argument -Wno-unused-parameter -Wwrite-strings -Wno-missing-field-initializers -Wno-long-long -Wno-maybe-uninitialized -Wno-class-memaccess -Wno-redundant-move -Wno-pessimizing-move -Wno-noexcept-type -Wno-comment -std=c++14 -fdeprecated-macro -fdebug-compilation-dir=/build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/build-llvm -fdebug-prefix-map=/build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/build-llvm=build-llvm -fdebug-prefix-map=/build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/= -ferror-limit 19 -fvisibility-inlines-hidden -stack-protector 2 -fgnuc-version=4.2.1 -fcolor-diagnostics -vectorize-loops -vectorize-slp -analyzer-output=html -analyzer-config stable-report-filename=true -faddrsig -D__GCC_HAVE_DWARF2_CFI_ASM=1 -o /tmp/scan-build-2022-03-19-125827-35351-1 -x c++ /build/llvm-toolchain-snapshot-15~++20220319111418+752e9cdbb06a/llvm/lib/Transforms/Vectorize/LoopVectorize.cpp
1//===- LoopVectorize.cpp - A Loop Vectorizer ------------------------------===//
2//
3// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4// See https://llvm.org/LICENSE.txt for license information.
5// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6//
7//===----------------------------------------------------------------------===//
8//
9// This is the LLVM loop vectorizer. This pass modifies 'vectorizable' loops
10// and generates target-independent LLVM-IR.
11// The vectorizer uses the TargetTransformInfo analysis to estimate the costs
12// of instructions in order to estimate the profitability of vectorization.
13//
14// The loop vectorizer combines consecutive loop iterations into a single
15// 'wide' iteration. After this transformation the index is incremented
16// by the SIMD vector width, and not by one.
17//
18// This pass has three parts:
19// 1. The main loop pass that drives the different parts.
20// 2. LoopVectorizationLegality - A unit that checks for the legality
21// of the vectorization.
22// 3. InnerLoopVectorizer - A unit that performs the actual
23// widening of instructions.
24// 4. LoopVectorizationCostModel - A unit that checks for the profitability
25// of vectorization. It decides on the optimal vector width, which
26// can be one, if vectorization is not profitable.
27//
28// There is a development effort going on to migrate loop vectorizer to the
29// VPlan infrastructure and to introduce outer loop vectorization support (see
30// docs/Proposal/VectorizationPlan.rst and
31// http://lists.llvm.org/pipermail/llvm-dev/2017-December/119523.html). For this
32// purpose, we temporarily introduced the VPlan-native vectorization path: an
33// alternative vectorization path that is natively implemented on top of the
34// VPlan infrastructure. See EnableVPlanNativePath for enabling.
35//
36//===----------------------------------------------------------------------===//
37//
38// The reduction-variable vectorization is based on the paper:
39// D. Nuzman and R. Henderson. Multi-platform Auto-vectorization.
40//
41// Variable uniformity checks are inspired by:
42// Karrenberg, R. and Hack, S. Whole Function Vectorization.
43//
44// The interleaved access vectorization is based on the paper:
45// Dorit Nuzman, Ira Rosen and Ayal Zaks. Auto-Vectorization of Interleaved
46// Data for SIMD
47//
48// Other ideas/concepts are from:
49// A. Zaks and D. Nuzman. Autovectorization in GCC-two years later.
50//
51// S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua. An Evaluation of
52// Vectorizing Compilers.
53//
54//===----------------------------------------------------------------------===//
55
56#include "llvm/Transforms/Vectorize/LoopVectorize.h"
57#include "LoopVectorizationPlanner.h"
58#include "VPRecipeBuilder.h"
59#include "VPlan.h"
60#include "VPlanHCFGBuilder.h"
61#include "VPlanPredicator.h"
62#include "VPlanTransforms.h"
63#include "llvm/ADT/APInt.h"
64#include "llvm/ADT/ArrayRef.h"
65#include "llvm/ADT/DenseMap.h"
66#include "llvm/ADT/DenseMapInfo.h"
67#include "llvm/ADT/Hashing.h"
68#include "llvm/ADT/MapVector.h"
69#include "llvm/ADT/None.h"
70#include "llvm/ADT/Optional.h"
71#include "llvm/ADT/STLExtras.h"
72#include "llvm/ADT/SmallPtrSet.h"
73#include "llvm/ADT/SmallSet.h"
74#include "llvm/ADT/SmallVector.h"
75#include "llvm/ADT/Statistic.h"
76#include "llvm/ADT/StringRef.h"
77#include "llvm/ADT/Twine.h"
78#include "llvm/ADT/iterator_range.h"
79#include "llvm/Analysis/AssumptionCache.h"
80#include "llvm/Analysis/BasicAliasAnalysis.h"
81#include "llvm/Analysis/BlockFrequencyInfo.h"
82#include "llvm/Analysis/CFG.h"
83#include "llvm/Analysis/CodeMetrics.h"
84#include "llvm/Analysis/DemandedBits.h"
85#include "llvm/Analysis/GlobalsModRef.h"
86#include "llvm/Analysis/LoopAccessAnalysis.h"
87#include "llvm/Analysis/LoopAnalysisManager.h"
88#include "llvm/Analysis/LoopInfo.h"
89#include "llvm/Analysis/LoopIterator.h"
90#include "llvm/Analysis/OptimizationRemarkEmitter.h"
91#include "llvm/Analysis/ProfileSummaryInfo.h"
92#include "llvm/Analysis/ScalarEvolution.h"
93#include "llvm/Analysis/ScalarEvolutionExpressions.h"
94#include "llvm/Analysis/TargetLibraryInfo.h"
95#include "llvm/Analysis/TargetTransformInfo.h"
96#include "llvm/Analysis/VectorUtils.h"
97#include "llvm/IR/Attributes.h"
98#include "llvm/IR/BasicBlock.h"
99#include "llvm/IR/CFG.h"
100#include "llvm/IR/Constant.h"
101#include "llvm/IR/Constants.h"
102#include "llvm/IR/DataLayout.h"
103#include "llvm/IR/DebugInfoMetadata.h"
104#include "llvm/IR/DebugLoc.h"
105#include "llvm/IR/DerivedTypes.h"
106#include "llvm/IR/DiagnosticInfo.h"
107#include "llvm/IR/Dominators.h"
108#include "llvm/IR/Function.h"
109#include "llvm/IR/IRBuilder.h"
110#include "llvm/IR/InstrTypes.h"
111#include "llvm/IR/Instruction.h"
112#include "llvm/IR/Instructions.h"
113#include "llvm/IR/IntrinsicInst.h"
114#include "llvm/IR/Intrinsics.h"
115#include "llvm/IR/Metadata.h"
116#include "llvm/IR/Module.h"
117#include "llvm/IR/Operator.h"
118#include "llvm/IR/PatternMatch.h"
119#include "llvm/IR/Type.h"
120#include "llvm/IR/Use.h"
121#include "llvm/IR/User.h"
122#include "llvm/IR/Value.h"
123#include "llvm/IR/ValueHandle.h"
124#include "llvm/IR/Verifier.h"
125#include "llvm/InitializePasses.h"
126#include "llvm/Pass.h"
127#include "llvm/Support/Casting.h"
128#include "llvm/Support/CommandLine.h"
129#include "llvm/Support/Compiler.h"
130#include "llvm/Support/Debug.h"
131#include "llvm/Support/ErrorHandling.h"
132#include "llvm/Support/InstructionCost.h"
133#include "llvm/Support/MathExtras.h"
134#include "llvm/Support/raw_ostream.h"
135#include "llvm/Transforms/Utils/BasicBlockUtils.h"
136#include "llvm/Transforms/Utils/InjectTLIMappings.h"
137#include "llvm/Transforms/Utils/LoopSimplify.h"
138#include "llvm/Transforms/Utils/LoopUtils.h"
139#include "llvm/Transforms/Utils/LoopVersioning.h"
140#include "llvm/Transforms/Utils/ScalarEvolutionExpander.h"
141#include "llvm/Transforms/Utils/SizeOpts.h"
142#include "llvm/Transforms/Vectorize/LoopVectorizationLegality.h"
143#include <algorithm>
144#include <cassert>
145#include <cstdint>
146#include <functional>
147#include <iterator>
148#include <limits>
149#include <memory>
150#include <string>
151#include <tuple>
152#include <utility>
153
154using namespace llvm;
155
156#define LV_NAME"loop-vectorize" "loop-vectorize"
157#define DEBUG_TYPE"loop-vectorize" LV_NAME"loop-vectorize"
158
159#ifndef NDEBUG
160const char VerboseDebug[] = DEBUG_TYPE"loop-vectorize" "-verbose";
161#endif
162
163/// @{
164/// Metadata attribute names
165const char LLVMLoopVectorizeFollowupAll[] = "llvm.loop.vectorize.followup_all";
166const char LLVMLoopVectorizeFollowupVectorized[] =
167 "llvm.loop.vectorize.followup_vectorized";
168const char LLVMLoopVectorizeFollowupEpilogue[] =
169 "llvm.loop.vectorize.followup_epilogue";
170/// @}
171
172STATISTIC(LoopsVectorized, "Number of loops vectorized")static llvm::Statistic LoopsVectorized = {"loop-vectorize", "LoopsVectorized"
, "Number of loops vectorized"}
;
173STATISTIC(LoopsAnalyzed, "Number of loops analyzed for vectorization")static llvm::Statistic LoopsAnalyzed = {"loop-vectorize", "LoopsAnalyzed"
, "Number of loops analyzed for vectorization"}
;
174STATISTIC(LoopsEpilogueVectorized, "Number of epilogues vectorized")static llvm::Statistic LoopsEpilogueVectorized = {"loop-vectorize"
, "LoopsEpilogueVectorized", "Number of epilogues vectorized"
}
;
175
176static cl::opt<bool> EnableEpilogueVectorization(
177 "enable-epilogue-vectorization", cl::init(true), cl::Hidden,
178 cl::desc("Enable vectorization of epilogue loops."));
179
180static cl::opt<unsigned> EpilogueVectorizationForceVF(
181 "epilogue-vectorization-force-VF", cl::init(1), cl::Hidden,
182 cl::desc("When epilogue vectorization is enabled, and a value greater than "
183 "1 is specified, forces the given VF for all applicable epilogue "
184 "loops."));
185
186static cl::opt<unsigned> EpilogueVectorizationMinVF(
187 "epilogue-vectorization-minimum-VF", cl::init(16), cl::Hidden,
188 cl::desc("Only loops with vectorization factor equal to or larger than "
189 "the specified value are considered for epilogue vectorization."));
190
191/// Loops with a known constant trip count below this number are vectorized only
192/// if no scalar iteration overheads are incurred.
193static cl::opt<unsigned> TinyTripCountVectorThreshold(
194 "vectorizer-min-trip-count", cl::init(16), cl::Hidden,
195 cl::desc("Loops with a constant trip count that is smaller than this "
196 "value are vectorized only if no scalar iteration overheads "
197 "are incurred."));
198
199static cl::opt<unsigned> PragmaVectorizeMemoryCheckThreshold(
200 "pragma-vectorize-memory-check-threshold", cl::init(128), cl::Hidden,
201 cl::desc("The maximum allowed number of runtime memory checks with a "
202 "vectorize(enable) pragma."));
203
204// Option prefer-predicate-over-epilogue indicates that an epilogue is undesired,
205// that predication is preferred, and this lists all options. I.e., the
206// vectorizer will try to fold the tail-loop (epilogue) into the vector body
207// and predicate the instructions accordingly. If tail-folding fails, there are
208// different fallback strategies depending on these values:
209namespace PreferPredicateTy {
210 enum Option {
211 ScalarEpilogue = 0,
212 PredicateElseScalarEpilogue,
213 PredicateOrDontVectorize
214 };
215} // namespace PreferPredicateTy
216
217static cl::opt<PreferPredicateTy::Option> PreferPredicateOverEpilogue(
218 "prefer-predicate-over-epilogue",
219 cl::init(PreferPredicateTy::ScalarEpilogue),
220 cl::Hidden,
221 cl::desc("Tail-folding and predication preferences over creating a scalar "
222 "epilogue loop."),
223 cl::values(clEnumValN(PreferPredicateTy::ScalarEpilogue,llvm::cl::OptionEnumValue { "scalar-epilogue", int(PreferPredicateTy
::ScalarEpilogue), "Don't tail-predicate loops, create scalar epilogue"
}
224 "scalar-epilogue",llvm::cl::OptionEnumValue { "scalar-epilogue", int(PreferPredicateTy
::ScalarEpilogue), "Don't tail-predicate loops, create scalar epilogue"
}
225 "Don't tail-predicate loops, create scalar epilogue")llvm::cl::OptionEnumValue { "scalar-epilogue", int(PreferPredicateTy
::ScalarEpilogue), "Don't tail-predicate loops, create scalar epilogue"
}
,
226 clEnumValN(PreferPredicateTy::PredicateElseScalarEpilogue,llvm::cl::OptionEnumValue { "predicate-else-scalar-epilogue",
int(PreferPredicateTy::PredicateElseScalarEpilogue), "prefer tail-folding, create scalar epilogue if tail "
"folding fails." }
227 "predicate-else-scalar-epilogue",llvm::cl::OptionEnumValue { "predicate-else-scalar-epilogue",
int(PreferPredicateTy::PredicateElseScalarEpilogue), "prefer tail-folding, create scalar epilogue if tail "
"folding fails." }
228 "prefer tail-folding, create scalar epilogue if tail "llvm::cl::OptionEnumValue { "predicate-else-scalar-epilogue",
int(PreferPredicateTy::PredicateElseScalarEpilogue), "prefer tail-folding, create scalar epilogue if tail "
"folding fails." }
229 "folding fails.")llvm::cl::OptionEnumValue { "predicate-else-scalar-epilogue",
int(PreferPredicateTy::PredicateElseScalarEpilogue), "prefer tail-folding, create scalar epilogue if tail "
"folding fails." }
,
230 clEnumValN(PreferPredicateTy::PredicateOrDontVectorize,llvm::cl::OptionEnumValue { "predicate-dont-vectorize", int(PreferPredicateTy
::PredicateOrDontVectorize), "prefers tail-folding, don't attempt vectorization if "
"tail-folding fails." }
231 "predicate-dont-vectorize",llvm::cl::OptionEnumValue { "predicate-dont-vectorize", int(PreferPredicateTy
::PredicateOrDontVectorize), "prefers tail-folding, don't attempt vectorization if "
"tail-folding fails." }
232 "prefers tail-folding, don't attempt vectorization if "llvm::cl::OptionEnumValue { "predicate-dont-vectorize", int(PreferPredicateTy
::PredicateOrDontVectorize), "prefers tail-folding, don't attempt vectorization if "
"tail-folding fails." }
233 "tail-folding fails.")llvm::cl::OptionEnumValue { "predicate-dont-vectorize", int(PreferPredicateTy
::PredicateOrDontVectorize), "prefers tail-folding, don't attempt vectorization if "
"tail-folding fails." }
));
234
235static cl::opt<bool> MaximizeBandwidth(
236 "vectorizer-maximize-bandwidth", cl::init(false), cl::Hidden,
237 cl::desc("Maximize bandwidth when selecting vectorization factor which "
238 "will be determined by the smallest type in loop."));
239
240static cl::opt<bool> EnableInterleavedMemAccesses(
241 "enable-interleaved-mem-accesses", cl::init(false), cl::Hidden,
242 cl::desc("Enable vectorization on interleaved memory accesses in a loop"));
243
244/// An interleave-group may need masking if it resides in a block that needs
245/// predication, or in order to mask away gaps.
246static cl::opt<bool> EnableMaskedInterleavedMemAccesses(
247 "enable-masked-interleaved-mem-accesses", cl::init(false), cl::Hidden,
248 cl::desc("Enable vectorization on masked interleaved memory accesses in a loop"));
249
250static cl::opt<unsigned> TinyTripCountInterleaveThreshold(
251 "tiny-trip-count-interleave-threshold", cl::init(128), cl::Hidden,
252 cl::desc("We don't interleave loops with a estimated constant trip count "
253 "below this number"));
254
255static cl::opt<unsigned> ForceTargetNumScalarRegs(
256 "force-target-num-scalar-regs", cl::init(0), cl::Hidden,
257 cl::desc("A flag that overrides the target's number of scalar registers."));
258
259static cl::opt<unsigned> ForceTargetNumVectorRegs(
260 "force-target-num-vector-regs", cl::init(0), cl::Hidden,
261 cl::desc("A flag that overrides the target's number of vector registers."));
262
263static cl::opt<unsigned> ForceTargetMaxScalarInterleaveFactor(
264 "force-target-max-scalar-interleave", cl::init(0), cl::Hidden,
265 cl::desc("A flag that overrides the target's max interleave factor for "
266 "scalar loops."));
267
268static cl::opt<unsigned> ForceTargetMaxVectorInterleaveFactor(
269 "force-target-max-vector-interleave", cl::init(0), cl::Hidden,
270 cl::desc("A flag that overrides the target's max interleave factor for "
271 "vectorized loops."));
272
273static cl::opt<unsigned> ForceTargetInstructionCost(
274 "force-target-instruction-cost", cl::init(0), cl::Hidden,
275 cl::desc("A flag that overrides the target's expected cost for "
276 "an instruction to a single constant value. Mostly "
277 "useful for getting consistent testing."));
278
279static cl::opt<bool> ForceTargetSupportsScalableVectors(
280 "force-target-supports-scalable-vectors", cl::init(false), cl::Hidden,
281 cl::desc(
282 "Pretend that scalable vectors are supported, even if the target does "
283 "not support them. This flag should only be used for testing."));
284
285static cl::opt<unsigned> SmallLoopCost(
286 "small-loop-cost", cl::init(20), cl::Hidden,
287 cl::desc(
288 "The cost of a loop that is considered 'small' by the interleaver."));
289
290static cl::opt<bool> LoopVectorizeWithBlockFrequency(
291 "loop-vectorize-with-block-frequency", cl::init(true), cl::Hidden,
292 cl::desc("Enable the use of the block frequency analysis to access PGO "
293 "heuristics minimizing code growth in cold regions and being more "
294 "aggressive in hot regions."));
295
296// Runtime interleave loops for load/store throughput.
297static cl::opt<bool> EnableLoadStoreRuntimeInterleave(
298 "enable-loadstore-runtime-interleave", cl::init(true), cl::Hidden,
299 cl::desc(
300 "Enable runtime interleaving until load/store ports are saturated"));
301
302/// Interleave small loops with scalar reductions.
303static cl::opt<bool> InterleaveSmallLoopScalarReduction(
304 "interleave-small-loop-scalar-reduction", cl::init(false), cl::Hidden,
305 cl::desc("Enable interleaving for loops with small iteration counts that "
306 "contain scalar reductions to expose ILP."));
307
308/// The number of stores in a loop that are allowed to need predication.
309static cl::opt<unsigned> NumberOfStoresToPredicate(
310 "vectorize-num-stores-pred", cl::init(1), cl::Hidden,
311 cl::desc("Max number of stores to be predicated behind an if."));
312
313static cl::opt<bool> EnableIndVarRegisterHeur(
314 "enable-ind-var-reg-heur", cl::init(true), cl::Hidden,
315 cl::desc("Count the induction variable only once when interleaving"));
316
317static cl::opt<bool> EnableCondStoresVectorization(
318 "enable-cond-stores-vec", cl::init(true), cl::Hidden,
319 cl::desc("Enable if predication of stores during vectorization."));
320
321static cl::opt<unsigned> MaxNestedScalarReductionIC(
322 "max-nested-scalar-reduction-interleave", cl::init(2), cl::Hidden,
323 cl::desc("The maximum interleave count to use when interleaving a scalar "
324 "reduction in a nested loop."));
325
326static cl::opt<bool>
327 PreferInLoopReductions("prefer-inloop-reductions", cl::init(false),
328 cl::Hidden,
329 cl::desc("Prefer in-loop vector reductions, "
330 "overriding the targets preference."));
331
332static cl::opt<bool> ForceOrderedReductions(
333 "force-ordered-reductions", cl::init(false), cl::Hidden,
334 cl::desc("Enable the vectorisation of loops with in-order (strict) "
335 "FP reductions"));
336
337static cl::opt<bool> PreferPredicatedReductionSelect(
338 "prefer-predicated-reduction-select", cl::init(false), cl::Hidden,
339 cl::desc(
340 "Prefer predicating a reduction operation over an after loop select."));
341
342cl::opt<bool> EnableVPlanNativePath(
343 "enable-vplan-native-path", cl::init(false), cl::Hidden,
344 cl::desc("Enable VPlan-native vectorization path with "
345 "support for outer loop vectorization."));
346
347// FIXME: Remove this switch once we have divergence analysis. Currently we
348// assume divergent non-backedge branches when this switch is true.
349cl::opt<bool> EnableVPlanPredication(
350 "enable-vplan-predication", cl::init(false), cl::Hidden,
351 cl::desc("Enable VPlan-native vectorization path predicator with "
352 "support for outer loop vectorization."));
353
354// This flag enables the stress testing of the VPlan H-CFG construction in the
355// VPlan-native vectorization path. It must be used in conjuction with
356// -enable-vplan-native-path. -vplan-verify-hcfg can also be used to enable the
357// verification of the H-CFGs built.
358static cl::opt<bool> VPlanBuildStressTest(
359 "vplan-build-stress-test", cl::init(false), cl::Hidden,
360 cl::desc(
361 "Build VPlan for every supported loop nest in the function and bail "
362 "out right after the build (stress test the VPlan H-CFG construction "
363 "in the VPlan-native vectorization path)."));
364
365cl::opt<bool> llvm::EnableLoopInterleaving(
366 "interleave-loops", cl::init(true), cl::Hidden,
367 cl::desc("Enable loop interleaving in Loop vectorization passes"));
368cl::opt<bool> llvm::EnableLoopVectorization(
369 "vectorize-loops", cl::init(true), cl::Hidden,
370 cl::desc("Run the Loop vectorization passes"));
371
372cl::opt<bool> PrintVPlansInDotFormat(
373 "vplan-print-in-dot-format", cl::init(false), cl::Hidden,
374 cl::desc("Use dot format instead of plain text when dumping VPlans"));
375
376/// A helper function that returns true if the given type is irregular. The
377/// type is irregular if its allocated size doesn't equal the store size of an
378/// element of the corresponding vector type.
379static bool hasIrregularType(Type *Ty, const DataLayout &DL) {
380 // Determine if an array of N elements of type Ty is "bitcast compatible"
381 // with a <N x Ty> vector.
382 // This is only true if there is no padding between the array elements.
383 return DL.getTypeAllocSizeInBits(Ty) != DL.getTypeSizeInBits(Ty);
384}
385
386/// A helper function that returns the reciprocal of the block probability of
387/// predicated blocks. If we return X, we are assuming the predicated block
388/// will execute once for every X iterations of the loop header.
389///
390/// TODO: We should use actual block probability here, if available. Currently,
391/// we always assume predicated blocks have a 50% chance of executing.
392static unsigned getReciprocalPredBlockProb() { return 2; }
393
394/// A helper function that returns an integer or floating-point constant with
395/// value C.
396static Constant *getSignedIntOrFpConstant(Type *Ty, int64_t C) {
397 return Ty->isIntegerTy() ? ConstantInt::getSigned(Ty, C)
398 : ConstantFP::get(Ty, C);
399}
400
401/// Returns "best known" trip count for the specified loop \p L as defined by
402/// the following procedure:
403/// 1) Returns exact trip count if it is known.
404/// 2) Returns expected trip count according to profile data if any.
405/// 3) Returns upper bound estimate if it is known.
406/// 4) Returns None if all of the above failed.
407static Optional<unsigned> getSmallBestKnownTC(ScalarEvolution &SE, Loop *L) {
408 // Check if exact trip count is known.
409 if (unsigned ExpectedTC = SE.getSmallConstantTripCount(L))
410 return ExpectedTC;
411
412 // Check if there is an expected trip count available from profile data.
413 if (LoopVectorizeWithBlockFrequency)
414 if (auto EstimatedTC = getLoopEstimatedTripCount(L))
415 return EstimatedTC;
416
417 // Check if upper bound estimate is known.
418 if (unsigned ExpectedTC = SE.getSmallConstantMaxTripCount(L))
419 return ExpectedTC;
420
421 return None;
422}
423
424// Forward declare GeneratedRTChecks.
425class GeneratedRTChecks;
426
427namespace llvm {
428
429AnalysisKey ShouldRunExtraVectorPasses::Key;
430
431/// InnerLoopVectorizer vectorizes loops which contain only one basic
432/// block to a specified vectorization factor (VF).
433/// This class performs the widening of scalars into vectors, or multiple
434/// scalars. This class also implements the following features:
435/// * It inserts an epilogue loop for handling loops that don't have iteration
436/// counts that are known to be a multiple of the vectorization factor.
437/// * It handles the code generation for reduction variables.
438/// * Scalarization (implementation using scalars) of un-vectorizable
439/// instructions.
440/// InnerLoopVectorizer does not perform any vectorization-legality
441/// checks, and relies on the caller to check for the different legality
442/// aspects. The InnerLoopVectorizer relies on the
443/// LoopVectorizationLegality class to provide information about the induction
444/// and reduction variables that were found to a given vectorization factor.
445class InnerLoopVectorizer {
446public:
447 InnerLoopVectorizer(Loop *OrigLoop, PredicatedScalarEvolution &PSE,
448 LoopInfo *LI, DominatorTree *DT,
449 const TargetLibraryInfo *TLI,
450 const TargetTransformInfo *TTI, AssumptionCache *AC,
451 OptimizationRemarkEmitter *ORE, ElementCount VecWidth,
452 unsigned UnrollFactor, LoopVectorizationLegality *LVL,
453 LoopVectorizationCostModel *CM, BlockFrequencyInfo *BFI,
454 ProfileSummaryInfo *PSI, GeneratedRTChecks &RTChecks)
455 : OrigLoop(OrigLoop), PSE(PSE), LI(LI), DT(DT), TLI(TLI), TTI(TTI),
456 AC(AC), ORE(ORE), VF(VecWidth), UF(UnrollFactor),
457 Builder(PSE.getSE()->getContext()), Legal(LVL), Cost(CM), BFI(BFI),
458 PSI(PSI), RTChecks(RTChecks) {
459 // Query this against the original loop and save it here because the profile
460 // of the original loop header may change as the transformation happens.
461 OptForSizeBasedOnProfile = llvm::shouldOptimizeForSize(
462 OrigLoop->getHeader(), PSI, BFI, PGSOQueryType::IRPass);
463 }
464
465 virtual ~InnerLoopVectorizer() = default;
466
467 /// Create a new empty loop that will contain vectorized instructions later
468 /// on, while the old loop will be used as the scalar remainder. Control flow
469 /// is generated around the vectorized (and scalar epilogue) loops consisting
470 /// of various checks and bypasses. Return the pre-header block of the new
471 /// loop and the start value for the canonical induction, if it is != 0. The
472 /// latter is the case when vectorizing the epilogue loop. In the case of
473 /// epilogue vectorization, this function is overriden to handle the more
474 /// complex control flow around the loops.
475 virtual std::pair<BasicBlock *, Value *> createVectorizedLoopSkeleton();
476
477 /// Widen a single call instruction within the innermost loop.
478 void widenCallInstruction(CallInst &I, VPValue *Def, VPUser &ArgOperands,
479 VPTransformState &State);
480
481 /// Fix the vectorized code, taking care of header phi's, live-outs, and more.
482 void fixVectorizedLoop(VPTransformState &State);
483
484 // Return true if any runtime check is added.
485 bool areSafetyChecksAdded() { return AddedSafetyChecks; }
486
487 /// A type for vectorized values in the new loop. Each value from the
488 /// original loop, when vectorized, is represented by UF vector values in the
489 /// new unrolled loop, where UF is the unroll factor.
490 using VectorParts = SmallVector<Value *, 2>;
491
492 /// Vectorize a single first-order recurrence or pointer induction PHINode in
493 /// a block. This method handles the induction variable canonicalization. It
494 /// supports both VF = 1 for unrolled loops and arbitrary length vectors.
495 void widenPHIInstruction(Instruction *PN, VPWidenPHIRecipe *PhiR,
496 VPTransformState &State);
497
498 /// A helper function to scalarize a single Instruction in the innermost loop.
499 /// Generates a sequence of scalar instances for each lane between \p MinLane
500 /// and \p MaxLane, times each part between \p MinPart and \p MaxPart,
501 /// inclusive. Uses the VPValue operands from \p RepRecipe instead of \p
502 /// Instr's operands.
503 void scalarizeInstruction(Instruction *Instr, VPReplicateRecipe *RepRecipe,
504 const VPIteration &Instance, bool IfPredicateInstr,
505 VPTransformState &State);
506
507 /// Construct the vector value of a scalarized value \p V one lane at a time.
508 void packScalarIntoVectorValue(VPValue *Def, const VPIteration &Instance,
509 VPTransformState &State);
510
511 /// Try to vectorize interleaved access group \p Group with the base address
512 /// given in \p Addr, optionally masking the vector operations if \p
513 /// BlockInMask is non-null. Use \p State to translate given VPValues to IR
514 /// values in the vectorized loop.
515 void vectorizeInterleaveGroup(const InterleaveGroup<Instruction> *Group,
516 ArrayRef<VPValue *> VPDefs,
517 VPTransformState &State, VPValue *Addr,
518 ArrayRef<VPValue *> StoredValues,
519 VPValue *BlockInMask = nullptr);
520
521 /// Set the debug location in the builder \p Ptr using the debug location in
522 /// \p V. If \p Ptr is None then it uses the class member's Builder.
523 void setDebugLocFromInst(const Value *V,
524 Optional<IRBuilderBase *> CustomBuilder = None);
525
526 /// Fix the non-induction PHIs in the OrigPHIsToFix vector.
527 void fixNonInductionPHIs(VPTransformState &State);
528
529 /// Returns true if the reordering of FP operations is not allowed, but we are
530 /// able to vectorize with strict in-order reductions for the given RdxDesc.
531 bool useOrderedReductions(const RecurrenceDescriptor &RdxDesc);
532
533 /// Create a broadcast instruction. This method generates a broadcast
534 /// instruction (shuffle) for loop invariant values and for the induction
535 /// value. If this is the induction variable then we extend it to N, N+1, ...
536 /// this is needed because each iteration in the loop corresponds to a SIMD
537 /// element.
538 virtual Value *getBroadcastInstrs(Value *V);
539
540 /// Add metadata from one instruction to another.
541 ///
542 /// This includes both the original MDs from \p From and additional ones (\see
543 /// addNewMetadata). Use this for *newly created* instructions in the vector
544 /// loop.
545 void addMetadata(Instruction *To, Instruction *From);
546
547 /// Similar to the previous function but it adds the metadata to a
548 /// vector of instructions.
549 void addMetadata(ArrayRef<Value *> To, Instruction *From);
550
551 // Returns the resume value (bc.merge.rdx) for a reduction as
552 // generated by fixReduction.
553 PHINode *getReductionResumeValue(const RecurrenceDescriptor &RdxDesc);
554
555protected:
556 friend class LoopVectorizationPlanner;
557
558 /// A small list of PHINodes.
559 using PhiVector = SmallVector<PHINode *, 4>;
560
561 /// A type for scalarized values in the new loop. Each value from the
562 /// original loop, when scalarized, is represented by UF x VF scalar values
563 /// in the new unrolled loop, where UF is the unroll factor and VF is the
564 /// vectorization factor.
565 using ScalarParts = SmallVector<SmallVector<Value *, 4>, 2>;
566
567 /// Set up the values of the IVs correctly when exiting the vector loop.
568 void fixupIVUsers(PHINode *OrigPhi, const InductionDescriptor &II,
569 Value *CountRoundDown, Value *EndValue,
570 BasicBlock *MiddleBlock, BasicBlock *VectorHeader);
571
572 /// Introduce a conditional branch (on true, condition to be set later) at the
573 /// end of the header=latch connecting it to itself (across the backedge) and
574 /// to the exit block of \p L.
575 void createHeaderBranch(Loop *L);
576
577 /// Handle all cross-iteration phis in the header.
578 void fixCrossIterationPHIs(VPTransformState &State);
579
580 /// Create the exit value of first order recurrences in the middle block and
581 /// update their users.
582 void fixFirstOrderRecurrence(VPFirstOrderRecurrencePHIRecipe *PhiR,
583 VPTransformState &State);
584
585 /// Create code for the loop exit value of the reduction.
586 void fixReduction(VPReductionPHIRecipe *Phi, VPTransformState &State);
587
588 /// Clear NSW/NUW flags from reduction instructions if necessary.
589 void clearReductionWrapFlags(const RecurrenceDescriptor &RdxDesc,
590 VPTransformState &State);
591
592 /// Fixup the LCSSA phi nodes in the unique exit block. This simply
593 /// means we need to add the appropriate incoming value from the middle
594 /// block as exiting edges from the scalar epilogue loop (if present) are
595 /// already in place, and we exit the vector loop exclusively to the middle
596 /// block.
597 void fixLCSSAPHIs(VPTransformState &State);
598
599 /// Iteratively sink the scalarized operands of a predicated instruction into
600 /// the block that was created for it.
601 void sinkScalarOperands(Instruction *PredInst);
602
603 /// Shrinks vector element sizes to the smallest bitwidth they can be legally
604 /// represented as.
605 void truncateToMinimalBitwidths(VPTransformState &State);
606
607 /// Returns (and creates if needed) the original loop trip count.
608 Value *getOrCreateTripCount(Loop *NewLoop);
609
610 /// Returns (and creates if needed) the trip count of the widened loop.
611 Value *getOrCreateVectorTripCount(Loop *NewLoop);
612
613 /// Returns a bitcasted value to the requested vector type.
614 /// Also handles bitcasts of vector<float> <-> vector<pointer> types.
615 Value *createBitOrPointerCast(Value *V, VectorType *DstVTy,
616 const DataLayout &DL);
617
618 /// Emit a bypass check to see if the vector trip count is zero, including if
619 /// it overflows.
620 void emitMinimumIterationCountCheck(Loop *L, BasicBlock *Bypass);
621
622 /// Emit a bypass check to see if all of the SCEV assumptions we've
623 /// had to make are correct. Returns the block containing the checks or
624 /// nullptr if no checks have been added.
625 BasicBlock *emitSCEVChecks(BasicBlock *Bypass);
626
627 /// Emit bypass checks to check any memory assumptions we may have made.
628 /// Returns the block containing the checks or nullptr if no checks have been
629 /// added.
630 BasicBlock *emitMemRuntimeChecks(Loop *L, BasicBlock *Bypass);
631
632 /// Emit basic blocks (prefixed with \p Prefix) for the iteration check,
633 /// vector loop preheader, middle block and scalar preheader. Also
634 /// allocate a loop object for the new vector loop and return it.
635 Loop *createVectorLoopSkeleton(StringRef Prefix);
636
637 /// Create new phi nodes for the induction variables to resume iteration count
638 /// in the scalar epilogue, from where the vectorized loop left off.
639 /// In cases where the loop skeleton is more complicated (eg. epilogue
640 /// vectorization) and the resume values can come from an additional bypass
641 /// block, the \p AdditionalBypass pair provides information about the bypass
642 /// block and the end value on the edge from bypass to this loop.
643 void createInductionResumeValues(
644 Loop *L,
645 std::pair<BasicBlock *, Value *> AdditionalBypass = {nullptr, nullptr});
646
647 /// Complete the loop skeleton by adding debug MDs, creating appropriate
648 /// conditional branches in the middle block, preparing the builder and
649 /// running the verifier. Take in the vector loop \p L as argument, and return
650 /// the preheader of the completed vector loop.
651 BasicBlock *completeLoopSkeleton(Loop *L, MDNode *OrigLoopID);
652
653 /// Add additional metadata to \p To that was not present on \p Orig.
654 ///
655 /// Currently this is used to add the noalias annotations based on the
656 /// inserted memchecks. Use this for instructions that are *cloned* into the
657 /// vector loop.
658 void addNewMetadata(Instruction *To, const Instruction *Orig);
659
660 /// Collect poison-generating recipes that may generate a poison value that is
661 /// used after vectorization, even when their operands are not poison. Those
662 /// recipes meet the following conditions:
663 /// * Contribute to the address computation of a recipe generating a widen
664 /// memory load/store (VPWidenMemoryInstructionRecipe or
665 /// VPInterleaveRecipe).
666 /// * Such a widen memory load/store has at least one underlying Instruction
667 /// that is in a basic block that needs predication and after vectorization
668 /// the generated instruction won't be predicated.
669 void collectPoisonGeneratingRecipes(VPTransformState &State);
670
671 /// Allow subclasses to override and print debug traces before/after vplan
672 /// execution, when trace information is requested.
673 virtual void printDebugTracesAtStart(){};
674 virtual void printDebugTracesAtEnd(){};
675
676 /// The original loop.
677 Loop *OrigLoop;
678
679 /// A wrapper around ScalarEvolution used to add runtime SCEV checks. Applies
680 /// dynamic knowledge to simplify SCEV expressions and converts them to a
681 /// more usable form.
682 PredicatedScalarEvolution &PSE;
683
684 /// Loop Info.
685 LoopInfo *LI;
686
687 /// Dominator Tree.
688 DominatorTree *DT;
689
690 /// Alias Analysis.
691 AAResults *AA;
692
693 /// Target Library Info.
694 const TargetLibraryInfo *TLI;
695
696 /// Target Transform Info.
697 const TargetTransformInfo *TTI;
698
699 /// Assumption Cache.
700 AssumptionCache *AC;
701
702 /// Interface to emit optimization remarks.
703 OptimizationRemarkEmitter *ORE;
704
705 /// LoopVersioning. It's only set up (non-null) if memchecks were
706 /// used.
707 ///
708 /// This is currently only used to add no-alias metadata based on the
709 /// memchecks. The actually versioning is performed manually.
710 std::unique_ptr<LoopVersioning> LVer;
711
712 /// The vectorization SIMD factor to use. Each vector will have this many
713 /// vector elements.
714 ElementCount VF;
715
716 /// The vectorization unroll factor to use. Each scalar is vectorized to this
717 /// many different vector instructions.
718 unsigned UF;
719
720 /// The builder that we use
721 IRBuilder<> Builder;
722
723 // --- Vectorization state ---
724
725 /// The vector-loop preheader.
726 BasicBlock *LoopVectorPreHeader;
727
728 /// The scalar-loop preheader.
729 BasicBlock *LoopScalarPreHeader;
730
731 /// Middle Block between the vector and the scalar.
732 BasicBlock *LoopMiddleBlock;
733
734 /// The unique ExitBlock of the scalar loop if one exists. Note that
735 /// there can be multiple exiting edges reaching this block.
736 BasicBlock *LoopExitBlock;
737
738 /// The scalar loop body.
739 BasicBlock *LoopScalarBody;
740
741 /// A list of all bypass blocks. The first block is the entry of the loop.
742 SmallVector<BasicBlock *, 4> LoopBypassBlocks;
743
744 /// Store instructions that were predicated.
745 SmallVector<Instruction *, 4> PredicatedInstructions;
746
747 /// Trip count of the original loop.
748 Value *TripCount = nullptr;
749
750 /// Trip count of the widened loop (TripCount - TripCount % (VF*UF))
751 Value *VectorTripCount = nullptr;
752
753 /// The legality analysis.
754 LoopVectorizationLegality *Legal;
755
756 /// The profitablity analysis.
757 LoopVectorizationCostModel *Cost;
758
759 // Record whether runtime checks are added.
760 bool AddedSafetyChecks = false;
761
762 // Holds the end values for each induction variable. We save the end values
763 // so we can later fix-up the external users of the induction variables.
764 DenseMap<PHINode *, Value *> IVEndValues;
765
766 // Vector of original scalar PHIs whose corresponding widened PHIs need to be
767 // fixed up at the end of vector code generation.
768 SmallVector<PHINode *, 8> OrigPHIsToFix;
769
770 /// BFI and PSI are used to check for profile guided size optimizations.
771 BlockFrequencyInfo *BFI;
772 ProfileSummaryInfo *PSI;
773
774 // Whether this loop should be optimized for size based on profile guided size
775 // optimizatios.
776 bool OptForSizeBasedOnProfile;
777
778 /// Structure to hold information about generated runtime checks, responsible
779 /// for cleaning the checks, if vectorization turns out unprofitable.
780 GeneratedRTChecks &RTChecks;
781
782 // Holds the resume values for reductions in the loops, used to set the
783 // correct start value of reduction PHIs when vectorizing the epilogue.
784 SmallMapVector<const RecurrenceDescriptor *, PHINode *, 4>
785 ReductionResumeValues;
786};
787
788class InnerLoopUnroller : public InnerLoopVectorizer {
789public:
790 InnerLoopUnroller(Loop *OrigLoop, PredicatedScalarEvolution &PSE,
791 LoopInfo *LI, DominatorTree *DT,
792 const TargetLibraryInfo *TLI,
793 const TargetTransformInfo *TTI, AssumptionCache *AC,
794 OptimizationRemarkEmitter *ORE, unsigned UnrollFactor,
795 LoopVectorizationLegality *LVL,
796 LoopVectorizationCostModel *CM, BlockFrequencyInfo *BFI,
797 ProfileSummaryInfo *PSI, GeneratedRTChecks &Check)
798 : InnerLoopVectorizer(OrigLoop, PSE, LI, DT, TLI, TTI, AC, ORE,
799 ElementCount::getFixed(1), UnrollFactor, LVL, CM,
800 BFI, PSI, Check) {}
801
802private:
803 Value *getBroadcastInstrs(Value *V) override;
804};
805
806/// Encapsulate information regarding vectorization of a loop and its epilogue.
807/// This information is meant to be updated and used across two stages of
808/// epilogue vectorization.
809struct EpilogueLoopVectorizationInfo {
810 ElementCount MainLoopVF = ElementCount::getFixed(0);
811 unsigned MainLoopUF = 0;
812 ElementCount EpilogueVF = ElementCount::getFixed(0);
813 unsigned EpilogueUF = 0;
814 BasicBlock *MainLoopIterationCountCheck = nullptr;
815 BasicBlock *EpilogueIterationCountCheck = nullptr;
816 BasicBlock *SCEVSafetyCheck = nullptr;
817 BasicBlock *MemSafetyCheck = nullptr;
818 Value *TripCount = nullptr;
819 Value *VectorTripCount = nullptr;
820
821 EpilogueLoopVectorizationInfo(ElementCount MVF, unsigned MUF,
822 ElementCount EVF, unsigned EUF)
823 : MainLoopVF(MVF), MainLoopUF(MUF), EpilogueVF(EVF), EpilogueUF(EUF) {
824 assert(EUF == 1 &&(static_cast <bool> (EUF == 1 && "A high UF for the epilogue loop is likely not beneficial."
) ? void (0) : __assert_fail ("EUF == 1 && \"A high UF for the epilogue loop is likely not beneficial.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 825, __extension__
__PRETTY_FUNCTION__))
825 "A high UF for the epilogue loop is likely not beneficial.")(static_cast <bool> (EUF == 1 && "A high UF for the epilogue loop is likely not beneficial."
) ? void (0) : __assert_fail ("EUF == 1 && \"A high UF for the epilogue loop is likely not beneficial.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 825, __extension__
__PRETTY_FUNCTION__))
;
826 }
827};
828
829/// An extension of the inner loop vectorizer that creates a skeleton for a
830/// vectorized loop that has its epilogue (residual) also vectorized.
831/// The idea is to run the vplan on a given loop twice, firstly to setup the
832/// skeleton and vectorize the main loop, and secondly to complete the skeleton
833/// from the first step and vectorize the epilogue. This is achieved by
834/// deriving two concrete strategy classes from this base class and invoking
835/// them in succession from the loop vectorizer planner.
836class InnerLoopAndEpilogueVectorizer : public InnerLoopVectorizer {
837public:
838 InnerLoopAndEpilogueVectorizer(
839 Loop *OrigLoop, PredicatedScalarEvolution &PSE, LoopInfo *LI,
840 DominatorTree *DT, const TargetLibraryInfo *TLI,
841 const TargetTransformInfo *TTI, AssumptionCache *AC,
842 OptimizationRemarkEmitter *ORE, EpilogueLoopVectorizationInfo &EPI,
843 LoopVectorizationLegality *LVL, llvm::LoopVectorizationCostModel *CM,
844 BlockFrequencyInfo *BFI, ProfileSummaryInfo *PSI,
845 GeneratedRTChecks &Checks)
846 : InnerLoopVectorizer(OrigLoop, PSE, LI, DT, TLI, TTI, AC, ORE,
847 EPI.MainLoopVF, EPI.MainLoopUF, LVL, CM, BFI, PSI,
848 Checks),
849 EPI(EPI) {}
850
851 // Override this function to handle the more complex control flow around the
852 // three loops.
853 std::pair<BasicBlock *, Value *>
854 createVectorizedLoopSkeleton() final override {
855 return createEpilogueVectorizedLoopSkeleton();
856 }
857
858 /// The interface for creating a vectorized skeleton using one of two
859 /// different strategies, each corresponding to one execution of the vplan
860 /// as described above.
861 virtual std::pair<BasicBlock *, Value *>
862 createEpilogueVectorizedLoopSkeleton() = 0;
863
864 /// Holds and updates state information required to vectorize the main loop
865 /// and its epilogue in two separate passes. This setup helps us avoid
866 /// regenerating and recomputing runtime safety checks. It also helps us to
867 /// shorten the iteration-count-check path length for the cases where the
868 /// iteration count of the loop is so small that the main vector loop is
869 /// completely skipped.
870 EpilogueLoopVectorizationInfo &EPI;
871};
872
873/// A specialized derived class of inner loop vectorizer that performs
874/// vectorization of *main* loops in the process of vectorizing loops and their
875/// epilogues.
876class EpilogueVectorizerMainLoop : public InnerLoopAndEpilogueVectorizer {
877public:
878 EpilogueVectorizerMainLoop(
879 Loop *OrigLoop, PredicatedScalarEvolution &PSE, LoopInfo *LI,
880 DominatorTree *DT, const TargetLibraryInfo *TLI,
881 const TargetTransformInfo *TTI, AssumptionCache *AC,
882 OptimizationRemarkEmitter *ORE, EpilogueLoopVectorizationInfo &EPI,
883 LoopVectorizationLegality *LVL, llvm::LoopVectorizationCostModel *CM,
884 BlockFrequencyInfo *BFI, ProfileSummaryInfo *PSI,
885 GeneratedRTChecks &Check)
886 : InnerLoopAndEpilogueVectorizer(OrigLoop, PSE, LI, DT, TLI, TTI, AC, ORE,
887 EPI, LVL, CM, BFI, PSI, Check) {}
888 /// Implements the interface for creating a vectorized skeleton using the
889 /// *main loop* strategy (ie the first pass of vplan execution).
890 std::pair<BasicBlock *, Value *>
891 createEpilogueVectorizedLoopSkeleton() final override;
892
893protected:
894 /// Emits an iteration count bypass check once for the main loop (when \p
895 /// ForEpilogue is false) and once for the epilogue loop (when \p
896 /// ForEpilogue is true).
897 BasicBlock *emitMinimumIterationCountCheck(Loop *L, BasicBlock *Bypass,
898 bool ForEpilogue);
899 void printDebugTracesAtStart() override;
900 void printDebugTracesAtEnd() override;
901};
902
903// A specialized derived class of inner loop vectorizer that performs
904// vectorization of *epilogue* loops in the process of vectorizing loops and
905// their epilogues.
906class EpilogueVectorizerEpilogueLoop : public InnerLoopAndEpilogueVectorizer {
907public:
908 EpilogueVectorizerEpilogueLoop(
909 Loop *OrigLoop, PredicatedScalarEvolution &PSE, LoopInfo *LI,
910 DominatorTree *DT, const TargetLibraryInfo *TLI,
911 const TargetTransformInfo *TTI, AssumptionCache *AC,
912 OptimizationRemarkEmitter *ORE, EpilogueLoopVectorizationInfo &EPI,
913 LoopVectorizationLegality *LVL, llvm::LoopVectorizationCostModel *CM,
914 BlockFrequencyInfo *BFI, ProfileSummaryInfo *PSI,
915 GeneratedRTChecks &Checks)
916 : InnerLoopAndEpilogueVectorizer(OrigLoop, PSE, LI, DT, TLI, TTI, AC, ORE,
917 EPI, LVL, CM, BFI, PSI, Checks) {}
918 /// Implements the interface for creating a vectorized skeleton using the
919 /// *epilogue loop* strategy (ie the second pass of vplan execution).
920 std::pair<BasicBlock *, Value *>
921 createEpilogueVectorizedLoopSkeleton() final override;
922
923protected:
924 /// Emits an iteration count bypass check after the main vector loop has
925 /// finished to see if there are any iterations left to execute by either
926 /// the vector epilogue or the scalar epilogue.
927 BasicBlock *emitMinimumVectorEpilogueIterCountCheck(
928 BasicBlock *Bypass,
929 BasicBlock *Insert);
930 void printDebugTracesAtStart() override;
931 void printDebugTracesAtEnd() override;
932};
933} // end namespace llvm
934
935/// Look for a meaningful debug location on the instruction or it's
936/// operands.
937static Instruction *getDebugLocFromInstOrOperands(Instruction *I) {
938 if (!I)
939 return I;
940
941 DebugLoc Empty;
942 if (I->getDebugLoc() != Empty)
943 return I;
944
945 for (Use &Op : I->operands()) {
946 if (Instruction *OpInst = dyn_cast<Instruction>(Op))
947 if (OpInst->getDebugLoc() != Empty)
948 return OpInst;
949 }
950
951 return I;
952}
953
954void InnerLoopVectorizer::setDebugLocFromInst(
955 const Value *V, Optional<IRBuilderBase *> CustomBuilder) {
956 IRBuilderBase *B = (CustomBuilder == None) ? &Builder : *CustomBuilder;
957 if (const Instruction *Inst = dyn_cast_or_null<Instruction>(V)) {
958 const DILocation *DIL = Inst->getDebugLoc();
959
960 // When a FSDiscriminator is enabled, we don't need to add the multiply
961 // factors to the discriminators.
962 if (DIL && Inst->getFunction()->isDebugInfoForProfiling() &&
963 !isa<DbgInfoIntrinsic>(Inst) && !EnableFSDiscriminator) {
964 // FIXME: For scalable vectors, assume vscale=1.
965 auto NewDIL =
966 DIL->cloneByMultiplyingDuplicationFactor(UF * VF.getKnownMinValue());
967 if (NewDIL)
968 B->SetCurrentDebugLocation(NewDIL.getValue());
969 else
970 LLVM_DEBUG(dbgs()do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "Failed to create new discriminator: "
<< DIL->getFilename() << " Line: " << DIL
->getLine(); } } while (false)
971 << "Failed to create new discriminator: "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "Failed to create new discriminator: "
<< DIL->getFilename() << " Line: " << DIL
->getLine(); } } while (false)
972 << DIL->getFilename() << " Line: " << DIL->getLine())do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "Failed to create new discriminator: "
<< DIL->getFilename() << " Line: " << DIL
->getLine(); } } while (false)
;
973 } else
974 B->SetCurrentDebugLocation(DIL);
975 } else
976 B->SetCurrentDebugLocation(DebugLoc());
977}
978
979/// Write a \p DebugMsg about vectorization to the debug output stream. If \p I
980/// is passed, the message relates to that particular instruction.
981#ifndef NDEBUG
982static void debugVectorizationMessage(const StringRef Prefix,
983 const StringRef DebugMsg,
984 Instruction *I) {
985 dbgs() << "LV: " << Prefix << DebugMsg;
986 if (I != nullptr)
987 dbgs() << " " << *I;
988 else
989 dbgs() << '.';
990 dbgs() << '\n';
991}
992#endif
993
994/// Create an analysis remark that explains why vectorization failed
995///
996/// \p PassName is the name of the pass (e.g. can be AlwaysPrint). \p
997/// RemarkName is the identifier for the remark. If \p I is passed it is an
998/// instruction that prevents vectorization. Otherwise \p TheLoop is used for
999/// the location of the remark. \return the remark object that can be
1000/// streamed to.
1001static OptimizationRemarkAnalysis createLVAnalysis(const char *PassName,
1002 StringRef RemarkName, Loop *TheLoop, Instruction *I) {
1003 Value *CodeRegion = TheLoop->getHeader();
1004 DebugLoc DL = TheLoop->getStartLoc();
1005
1006 if (I) {
1007 CodeRegion = I->getParent();
1008 // If there is no debug location attached to the instruction, revert back to
1009 // using the loop's.
1010 if (I->getDebugLoc())
1011 DL = I->getDebugLoc();
1012 }
1013
1014 return OptimizationRemarkAnalysis(PassName, RemarkName, DL, CodeRegion);
1015}
1016
1017namespace llvm {
1018
1019/// Return a value for Step multiplied by VF.
1020Value *createStepForVF(IRBuilderBase &B, Type *Ty, ElementCount VF,
1021 int64_t Step) {
1022 assert(Ty->isIntegerTy() && "Expected an integer step")(static_cast <bool> (Ty->isIntegerTy() && "Expected an integer step"
) ? void (0) : __assert_fail ("Ty->isIntegerTy() && \"Expected an integer step\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1022, __extension__
__PRETTY_FUNCTION__))
;
1023 Constant *StepVal = ConstantInt::get(Ty, Step * VF.getKnownMinValue());
1024 return VF.isScalable() ? B.CreateVScale(StepVal) : StepVal;
1025}
1026
1027/// Return the runtime value for VF.
1028Value *getRuntimeVF(IRBuilderBase &B, Type *Ty, ElementCount VF) {
1029 Constant *EC = ConstantInt::get(Ty, VF.getKnownMinValue());
1030 return VF.isScalable() ? B.CreateVScale(EC) : EC;
1031}
1032
1033static Value *getRuntimeVFAsFloat(IRBuilderBase &B, Type *FTy,
1034 ElementCount VF) {
1035 assert(FTy->isFloatingPointTy() && "Expected floating point type!")(static_cast <bool> (FTy->isFloatingPointTy() &&
"Expected floating point type!") ? void (0) : __assert_fail (
"FTy->isFloatingPointTy() && \"Expected floating point type!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1035, __extension__
__PRETTY_FUNCTION__))
;
1036 Type *IntTy = IntegerType::get(FTy->getContext(), FTy->getScalarSizeInBits());
1037 Value *RuntimeVF = getRuntimeVF(B, IntTy, VF);
1038 return B.CreateUIToFP(RuntimeVF, FTy);
1039}
1040
1041void reportVectorizationFailure(const StringRef DebugMsg,
1042 const StringRef OREMsg, const StringRef ORETag,
1043 OptimizationRemarkEmitter *ORE, Loop *TheLoop,
1044 Instruction *I) {
1045 LLVM_DEBUG(debugVectorizationMessage("Not vectorizing: ", DebugMsg, I))do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { debugVectorizationMessage("Not vectorizing: "
, DebugMsg, I); } } while (false)
;
1046 LoopVectorizeHints Hints(TheLoop, true /* doesn't matter */, *ORE);
1047 ORE->emit(
1048 createLVAnalysis(Hints.vectorizeAnalysisPassName(), ORETag, TheLoop, I)
1049 << "loop not vectorized: " << OREMsg);
1050}
1051
1052void reportVectorizationInfo(const StringRef Msg, const StringRef ORETag,
1053 OptimizationRemarkEmitter *ORE, Loop *TheLoop,
1054 Instruction *I) {
1055 LLVM_DEBUG(debugVectorizationMessage("", Msg, I))do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { debugVectorizationMessage("", Msg, I); }
} while (false)
;
1056 LoopVectorizeHints Hints(TheLoop, true /* doesn't matter */, *ORE);
1057 ORE->emit(
1058 createLVAnalysis(Hints.vectorizeAnalysisPassName(), ORETag, TheLoop, I)
1059 << Msg);
1060}
1061
1062} // end namespace llvm
1063
1064#ifndef NDEBUG
1065/// \return string containing a file name and a line # for the given loop.
1066static std::string getDebugLocString(const Loop *L) {
1067 std::string Result;
1068 if (L) {
1069 raw_string_ostream OS(Result);
1070 if (const DebugLoc LoopDbgLoc = L->getStartLoc())
1071 LoopDbgLoc.print(OS);
1072 else
1073 // Just print the module name.
1074 OS << L->getHeader()->getParent()->getParent()->getModuleIdentifier();
1075 OS.flush();
1076 }
1077 return Result;
1078}
1079#endif
1080
1081void InnerLoopVectorizer::addNewMetadata(Instruction *To,
1082 const Instruction *Orig) {
1083 // If the loop was versioned with memchecks, add the corresponding no-alias
1084 // metadata.
1085 if (LVer && (isa<LoadInst>(Orig) || isa<StoreInst>(Orig)))
1086 LVer->annotateInstWithNoAlias(To, Orig);
1087}
1088
1089void InnerLoopVectorizer::collectPoisonGeneratingRecipes(
1090 VPTransformState &State) {
1091
1092 // Collect recipes in the backward slice of `Root` that may generate a poison
1093 // value that is used after vectorization.
1094 SmallPtrSet<VPRecipeBase *, 16> Visited;
1095 auto collectPoisonGeneratingInstrsInBackwardSlice([&](VPRecipeBase *Root) {
1096 SmallVector<VPRecipeBase *, 16> Worklist;
1097 Worklist.push_back(Root);
1098
1099 // Traverse the backward slice of Root through its use-def chain.
1100 while (!Worklist.empty()) {
1101 VPRecipeBase *CurRec = Worklist.back();
1102 Worklist.pop_back();
1103
1104 if (!Visited.insert(CurRec).second)
1105 continue;
1106
1107 // Prune search if we find another recipe generating a widen memory
1108 // instruction. Widen memory instructions involved in address computation
1109 // will lead to gather/scatter instructions, which don't need to be
1110 // handled.
1111 if (isa<VPWidenMemoryInstructionRecipe>(CurRec) ||
1112 isa<VPInterleaveRecipe>(CurRec) ||
1113 isa<VPScalarIVStepsRecipe>(CurRec) ||
1114 isa<VPCanonicalIVPHIRecipe>(CurRec))
1115 continue;
1116
1117 // This recipe contributes to the address computation of a widen
1118 // load/store. Collect recipe if its underlying instruction has
1119 // poison-generating flags.
1120 Instruction *Instr = CurRec->getUnderlyingInstr();
1121 if (Instr && Instr->hasPoisonGeneratingFlags())
1122 State.MayGeneratePoisonRecipes.insert(CurRec);
1123
1124 // Add new definitions to the worklist.
1125 for (VPValue *operand : CurRec->operands())
1126 if (VPDef *OpDef = operand->getDef())
1127 Worklist.push_back(cast<VPRecipeBase>(OpDef));
1128 }
1129 });
1130
1131 // Traverse all the recipes in the VPlan and collect the poison-generating
1132 // recipes in the backward slice starting at the address of a VPWidenRecipe or
1133 // VPInterleaveRecipe.
1134 auto Iter = depth_first(
1135 VPBlockRecursiveTraversalWrapper<VPBlockBase *>(State.Plan->getEntry()));
1136 for (VPBasicBlock *VPBB : VPBlockUtils::blocksOnly<VPBasicBlock>(Iter)) {
1137 for (VPRecipeBase &Recipe : *VPBB) {
1138 if (auto *WidenRec = dyn_cast<VPWidenMemoryInstructionRecipe>(&Recipe)) {
1139 Instruction *UnderlyingInstr = WidenRec->getUnderlyingInstr();
1140 VPDef *AddrDef = WidenRec->getAddr()->getDef();
1141 if (AddrDef && WidenRec->isConsecutive() && UnderlyingInstr &&
1142 Legal->blockNeedsPredication(UnderlyingInstr->getParent()))
1143 collectPoisonGeneratingInstrsInBackwardSlice(
1144 cast<VPRecipeBase>(AddrDef));
1145 } else if (auto *InterleaveRec = dyn_cast<VPInterleaveRecipe>(&Recipe)) {
1146 VPDef *AddrDef = InterleaveRec->getAddr()->getDef();
1147 if (AddrDef) {
1148 // Check if any member of the interleave group needs predication.
1149 const InterleaveGroup<Instruction> *InterGroup =
1150 InterleaveRec->getInterleaveGroup();
1151 bool NeedPredication = false;
1152 for (int I = 0, NumMembers = InterGroup->getNumMembers();
1153 I < NumMembers; ++I) {
1154 Instruction *Member = InterGroup->getMember(I);
1155 if (Member)
1156 NeedPredication |=
1157 Legal->blockNeedsPredication(Member->getParent());
1158 }
1159
1160 if (NeedPredication)
1161 collectPoisonGeneratingInstrsInBackwardSlice(
1162 cast<VPRecipeBase>(AddrDef));
1163 }
1164 }
1165 }
1166 }
1167}
1168
1169void InnerLoopVectorizer::addMetadata(Instruction *To,
1170 Instruction *From) {
1171 propagateMetadata(To, From);
1172 addNewMetadata(To, From);
1173}
1174
1175void InnerLoopVectorizer::addMetadata(ArrayRef<Value *> To,
1176 Instruction *From) {
1177 for (Value *V : To) {
1178 if (Instruction *I = dyn_cast<Instruction>(V))
1179 addMetadata(I, From);
1180 }
1181}
1182
1183PHINode *InnerLoopVectorizer::getReductionResumeValue(
1184 const RecurrenceDescriptor &RdxDesc) {
1185 auto It = ReductionResumeValues.find(&RdxDesc);
1186 assert(It != ReductionResumeValues.end() &&(static_cast <bool> (It != ReductionResumeValues.end() &&
"Expected to find a resume value for the reduction.") ? void
(0) : __assert_fail ("It != ReductionResumeValues.end() && \"Expected to find a resume value for the reduction.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1187, __extension__
__PRETTY_FUNCTION__))
1187 "Expected to find a resume value for the reduction.")(static_cast <bool> (It != ReductionResumeValues.end() &&
"Expected to find a resume value for the reduction.") ? void
(0) : __assert_fail ("It != ReductionResumeValues.end() && \"Expected to find a resume value for the reduction.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1187, __extension__
__PRETTY_FUNCTION__))
;
1188 return It->second;
1189}
1190
1191namespace llvm {
1192
1193// Loop vectorization cost-model hints how the scalar epilogue loop should be
1194// lowered.
1195enum ScalarEpilogueLowering {
1196
1197 // The default: allowing scalar epilogues.
1198 CM_ScalarEpilogueAllowed,
1199
1200 // Vectorization with OptForSize: don't allow epilogues.
1201 CM_ScalarEpilogueNotAllowedOptSize,
1202
1203 // A special case of vectorisation with OptForSize: loops with a very small
1204 // trip count are considered for vectorization under OptForSize, thereby
1205 // making sure the cost of their loop body is dominant, free of runtime
1206 // guards and scalar iteration overheads.
1207 CM_ScalarEpilogueNotAllowedLowTripLoop,
1208
1209 // Loop hint predicate indicating an epilogue is undesired.
1210 CM_ScalarEpilogueNotNeededUsePredicate,
1211
1212 // Directive indicating we must either tail fold or not vectorize
1213 CM_ScalarEpilogueNotAllowedUsePredicate
1214};
1215
1216/// ElementCountComparator creates a total ordering for ElementCount
1217/// for the purposes of using it in a set structure.
1218struct ElementCountComparator {
1219 bool operator()(const ElementCount &LHS, const ElementCount &RHS) const {
1220 return std::make_tuple(LHS.isScalable(), LHS.getKnownMinValue()) <
1221 std::make_tuple(RHS.isScalable(), RHS.getKnownMinValue());
1222 }
1223};
1224using ElementCountSet = SmallSet<ElementCount, 16, ElementCountComparator>;
1225
1226/// LoopVectorizationCostModel - estimates the expected speedups due to
1227/// vectorization.
1228/// In many cases vectorization is not profitable. This can happen because of
1229/// a number of reasons. In this class we mainly attempt to predict the
1230/// expected speedup/slowdowns due to the supported instruction set. We use the
1231/// TargetTransformInfo to query the different backends for the cost of
1232/// different operations.
1233class LoopVectorizationCostModel {
1234public:
1235 LoopVectorizationCostModel(ScalarEpilogueLowering SEL, Loop *L,
1236 PredicatedScalarEvolution &PSE, LoopInfo *LI,
1237 LoopVectorizationLegality *Legal,
1238 const TargetTransformInfo &TTI,
1239 const TargetLibraryInfo *TLI, DemandedBits *DB,
1240 AssumptionCache *AC,
1241 OptimizationRemarkEmitter *ORE, const Function *F,
1242 const LoopVectorizeHints *Hints,
1243 InterleavedAccessInfo &IAI)
1244 : ScalarEpilogueStatus(SEL), TheLoop(L), PSE(PSE), LI(LI), Legal(Legal),
1245 TTI(TTI), TLI(TLI), DB(DB), AC(AC), ORE(ORE), TheFunction(F),
1246 Hints(Hints), InterleaveInfo(IAI) {}
1247
1248 /// \return An upper bound for the vectorization factors (both fixed and
1249 /// scalable). If the factors are 0, vectorization and interleaving should be
1250 /// avoided up front.
1251 FixedScalableVFPair computeMaxVF(ElementCount UserVF, unsigned UserIC);
1252
1253 /// \return True if runtime checks are required for vectorization, and false
1254 /// otherwise.
1255 bool runtimeChecksRequired();
1256
1257 /// \return The most profitable vectorization factor and the cost of that VF.
1258 /// This method checks every VF in \p CandidateVFs. If UserVF is not ZERO
1259 /// then this vectorization factor will be selected if vectorization is
1260 /// possible.
1261 VectorizationFactor
1262 selectVectorizationFactor(const ElementCountSet &CandidateVFs);
1263
1264 VectorizationFactor
1265 selectEpilogueVectorizationFactor(const ElementCount MaxVF,
1266 const LoopVectorizationPlanner &LVP);
1267
1268 /// Setup cost-based decisions for user vectorization factor.
1269 /// \return true if the UserVF is a feasible VF to be chosen.
1270 bool selectUserVectorizationFactor(ElementCount UserVF) {
1271 collectUniformsAndScalars(UserVF);
1272 collectInstsToScalarize(UserVF);
1273 return expectedCost(UserVF).first.isValid();
1274 }
1275
1276 /// \return The size (in bits) of the smallest and widest types in the code
1277 /// that needs to be vectorized. We ignore values that remain scalar such as
1278 /// 64 bit loop indices.
1279 std::pair<unsigned, unsigned> getSmallestAndWidestTypes();
1280
1281 /// \return The desired interleave count.
1282 /// If interleave count has been specified by metadata it will be returned.
1283 /// Otherwise, the interleave count is computed and returned. VF and LoopCost
1284 /// are the selected vectorization factor and the cost of the selected VF.
1285 unsigned selectInterleaveCount(ElementCount VF, unsigned LoopCost);
1286
1287 /// Memory access instruction may be vectorized in more than one way.
1288 /// Form of instruction after vectorization depends on cost.
1289 /// This function takes cost-based decisions for Load/Store instructions
1290 /// and collects them in a map. This decisions map is used for building
1291 /// the lists of loop-uniform and loop-scalar instructions.
1292 /// The calculated cost is saved with widening decision in order to
1293 /// avoid redundant calculations.
1294 void setCostBasedWideningDecision(ElementCount VF);
1295
1296 /// A struct that represents some properties of the register usage
1297 /// of a loop.
1298 struct RegisterUsage {
1299 /// Holds the number of loop invariant values that are used in the loop.
1300 /// The key is ClassID of target-provided register class.
1301 SmallMapVector<unsigned, unsigned, 4> LoopInvariantRegs;
1302 /// Holds the maximum number of concurrent live intervals in the loop.
1303 /// The key is ClassID of target-provided register class.
1304 SmallMapVector<unsigned, unsigned, 4> MaxLocalUsers;
1305 };
1306
1307 /// \return Returns information about the register usages of the loop for the
1308 /// given vectorization factors.
1309 SmallVector<RegisterUsage, 8>
1310 calculateRegisterUsage(ArrayRef<ElementCount> VFs);
1311
1312 /// Collect values we want to ignore in the cost model.
1313 void collectValuesToIgnore();
1314
1315 /// Collect all element types in the loop for which widening is needed.
1316 void collectElementTypesForWidening();
1317
1318 /// Split reductions into those that happen in the loop, and those that happen
1319 /// outside. In loop reductions are collected into InLoopReductionChains.
1320 void collectInLoopReductions();
1321
1322 /// Returns true if we should use strict in-order reductions for the given
1323 /// RdxDesc. This is true if the -enable-strict-reductions flag is passed,
1324 /// the IsOrdered flag of RdxDesc is set and we do not allow reordering
1325 /// of FP operations.
1326 bool useOrderedReductions(const RecurrenceDescriptor &RdxDesc) {
1327 return !Hints->allowReordering() && RdxDesc.isOrdered();
1328 }
1329
1330 /// \returns The smallest bitwidth each instruction can be represented with.
1331 /// The vector equivalents of these instructions should be truncated to this
1332 /// type.
1333 const MapVector<Instruction *, uint64_t> &getMinimalBitwidths() const {
1334 return MinBWs;
1335 }
1336
1337 /// \returns True if it is more profitable to scalarize instruction \p I for
1338 /// vectorization factor \p VF.
1339 bool isProfitableToScalarize(Instruction *I, ElementCount VF) const {
1340 assert(VF.isVector() &&(static_cast <bool> (VF.isVector() && "Profitable to scalarize relevant only for VF > 1."
) ? void (0) : __assert_fail ("VF.isVector() && \"Profitable to scalarize relevant only for VF > 1.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1341, __extension__
__PRETTY_FUNCTION__))
1341 "Profitable to scalarize relevant only for VF > 1.")(static_cast <bool> (VF.isVector() && "Profitable to scalarize relevant only for VF > 1."
) ? void (0) : __assert_fail ("VF.isVector() && \"Profitable to scalarize relevant only for VF > 1.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1341, __extension__
__PRETTY_FUNCTION__))
;
1342
1343 // Cost model is not run in the VPlan-native path - return conservative
1344 // result until this changes.
1345 if (EnableVPlanNativePath)
1346 return false;
1347
1348 auto Scalars = InstsToScalarize.find(VF);
1349 assert(Scalars != InstsToScalarize.end() &&(static_cast <bool> (Scalars != InstsToScalarize.end() &&
"VF not yet analyzed for scalarization profitability") ? void
(0) : __assert_fail ("Scalars != InstsToScalarize.end() && \"VF not yet analyzed for scalarization profitability\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1350, __extension__
__PRETTY_FUNCTION__))
1350 "VF not yet analyzed for scalarization profitability")(static_cast <bool> (Scalars != InstsToScalarize.end() &&
"VF not yet analyzed for scalarization profitability") ? void
(0) : __assert_fail ("Scalars != InstsToScalarize.end() && \"VF not yet analyzed for scalarization profitability\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1350, __extension__
__PRETTY_FUNCTION__))
;
1351 return Scalars->second.find(I) != Scalars->second.end();
1352 }
1353
1354 /// Returns true if \p I is known to be uniform after vectorization.
1355 bool isUniformAfterVectorization(Instruction *I, ElementCount VF) const {
1356 if (VF.isScalar())
1357 return true;
1358
1359 // Cost model is not run in the VPlan-native path - return conservative
1360 // result until this changes.
1361 if (EnableVPlanNativePath)
1362 return false;
1363
1364 auto UniformsPerVF = Uniforms.find(VF);
1365 assert(UniformsPerVF != Uniforms.end() &&(static_cast <bool> (UniformsPerVF != Uniforms.end() &&
"VF not yet analyzed for uniformity") ? void (0) : __assert_fail
("UniformsPerVF != Uniforms.end() && \"VF not yet analyzed for uniformity\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1366, __extension__
__PRETTY_FUNCTION__))
1366 "VF not yet analyzed for uniformity")(static_cast <bool> (UniformsPerVF != Uniforms.end() &&
"VF not yet analyzed for uniformity") ? void (0) : __assert_fail
("UniformsPerVF != Uniforms.end() && \"VF not yet analyzed for uniformity\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1366, __extension__
__PRETTY_FUNCTION__))
;
1367 return UniformsPerVF->second.count(I);
1368 }
1369
1370 /// Returns true if \p I is known to be scalar after vectorization.
1371 bool isScalarAfterVectorization(Instruction *I, ElementCount VF) const {
1372 if (VF.isScalar())
1373 return true;
1374
1375 // Cost model is not run in the VPlan-native path - return conservative
1376 // result until this changes.
1377 if (EnableVPlanNativePath)
1378 return false;
1379
1380 auto ScalarsPerVF = Scalars.find(VF);
1381 assert(ScalarsPerVF != Scalars.end() &&(static_cast <bool> (ScalarsPerVF != Scalars.end() &&
"Scalar values are not calculated for VF") ? void (0) : __assert_fail
("ScalarsPerVF != Scalars.end() && \"Scalar values are not calculated for VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1382, __extension__
__PRETTY_FUNCTION__))
1382 "Scalar values are not calculated for VF")(static_cast <bool> (ScalarsPerVF != Scalars.end() &&
"Scalar values are not calculated for VF") ? void (0) : __assert_fail
("ScalarsPerVF != Scalars.end() && \"Scalar values are not calculated for VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1382, __extension__
__PRETTY_FUNCTION__))
;
1383 return ScalarsPerVF->second.count(I);
1384 }
1385
1386 /// \returns True if instruction \p I can be truncated to a smaller bitwidth
1387 /// for vectorization factor \p VF.
1388 bool canTruncateToMinimalBitwidth(Instruction *I, ElementCount VF) const {
1389 return VF.isVector() && MinBWs.find(I) != MinBWs.end() &&
1390 !isProfitableToScalarize(I, VF) &&
1391 !isScalarAfterVectorization(I, VF);
1392 }
1393
1394 /// Decision that was taken during cost calculation for memory instruction.
1395 enum InstWidening {
1396 CM_Unknown,
1397 CM_Widen, // For consecutive accesses with stride +1.
1398 CM_Widen_Reverse, // For consecutive accesses with stride -1.
1399 CM_Interleave,
1400 CM_GatherScatter,
1401 CM_Scalarize
1402 };
1403
1404 /// Save vectorization decision \p W and \p Cost taken by the cost model for
1405 /// instruction \p I and vector width \p VF.
1406 void setWideningDecision(Instruction *I, ElementCount VF, InstWidening W,
1407 InstructionCost Cost) {
1408 assert(VF.isVector() && "Expected VF >=2")(static_cast <bool> (VF.isVector() && "Expected VF >=2"
) ? void (0) : __assert_fail ("VF.isVector() && \"Expected VF >=2\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1408, __extension__
__PRETTY_FUNCTION__))
;
1409 WideningDecisions[std::make_pair(I, VF)] = std::make_pair(W, Cost);
1410 }
1411
1412 /// Save vectorization decision \p W and \p Cost taken by the cost model for
1413 /// interleaving group \p Grp and vector width \p VF.
1414 void setWideningDecision(const InterleaveGroup<Instruction> *Grp,
1415 ElementCount VF, InstWidening W,
1416 InstructionCost Cost) {
1417 assert(VF.isVector() && "Expected VF >=2")(static_cast <bool> (VF.isVector() && "Expected VF >=2"
) ? void (0) : __assert_fail ("VF.isVector() && \"Expected VF >=2\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1417, __extension__
__PRETTY_FUNCTION__))
;
1418 /// Broadcast this decicion to all instructions inside the group.
1419 /// But the cost will be assigned to one instruction only.
1420 for (unsigned i = 0; i < Grp->getFactor(); ++i) {
1421 if (auto *I = Grp->getMember(i)) {
1422 if (Grp->getInsertPos() == I)
1423 WideningDecisions[std::make_pair(I, VF)] = std::make_pair(W, Cost);
1424 else
1425 WideningDecisions[std::make_pair(I, VF)] = std::make_pair(W, 0);
1426 }
1427 }
1428 }
1429
1430 /// Return the cost model decision for the given instruction \p I and vector
1431 /// width \p VF. Return CM_Unknown if this instruction did not pass
1432 /// through the cost modeling.
1433 InstWidening getWideningDecision(Instruction *I, ElementCount VF) const {
1434 assert(VF.isVector() && "Expected VF to be a vector VF")(static_cast <bool> (VF.isVector() && "Expected VF to be a vector VF"
) ? void (0) : __assert_fail ("VF.isVector() && \"Expected VF to be a vector VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1434, __extension__
__PRETTY_FUNCTION__))
;
1435 // Cost model is not run in the VPlan-native path - return conservative
1436 // result until this changes.
1437 if (EnableVPlanNativePath)
1438 return CM_GatherScatter;
1439
1440 std::pair<Instruction *, ElementCount> InstOnVF = std::make_pair(I, VF);
1441 auto Itr = WideningDecisions.find(InstOnVF);
1442 if (Itr == WideningDecisions.end())
1443 return CM_Unknown;
1444 return Itr->second.first;
1445 }
1446
1447 /// Return the vectorization cost for the given instruction \p I and vector
1448 /// width \p VF.
1449 InstructionCost getWideningCost(Instruction *I, ElementCount VF) {
1450 assert(VF.isVector() && "Expected VF >=2")(static_cast <bool> (VF.isVector() && "Expected VF >=2"
) ? void (0) : __assert_fail ("VF.isVector() && \"Expected VF >=2\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1450, __extension__
__PRETTY_FUNCTION__))
;
1451 std::pair<Instruction *, ElementCount> InstOnVF = std::make_pair(I, VF);
1452 assert(WideningDecisions.find(InstOnVF) != WideningDecisions.end() &&(static_cast <bool> (WideningDecisions.find(InstOnVF) !=
WideningDecisions.end() && "The cost is not calculated"
) ? void (0) : __assert_fail ("WideningDecisions.find(InstOnVF) != WideningDecisions.end() && \"The cost is not calculated\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1453, __extension__
__PRETTY_FUNCTION__))
1453 "The cost is not calculated")(static_cast <bool> (WideningDecisions.find(InstOnVF) !=
WideningDecisions.end() && "The cost is not calculated"
) ? void (0) : __assert_fail ("WideningDecisions.find(InstOnVF) != WideningDecisions.end() && \"The cost is not calculated\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 1453, __extension__
__PRETTY_FUNCTION__))
;
1454 return WideningDecisions[InstOnVF].second;
1455 }
1456
1457 /// Return True if instruction \p I is an optimizable truncate whose operand
1458 /// is an induction variable. Such a truncate will be removed by adding a new
1459 /// induction variable with the destination type.
1460 bool isOptimizableIVTruncate(Instruction *I, ElementCount VF) {
1461 // If the instruction is not a truncate, return false.
1462 auto *Trunc = dyn_cast<TruncInst>(I);
1463 if (!Trunc)
1464 return false;
1465
1466 // Get the source and destination types of the truncate.
1467 Type *SrcTy = ToVectorTy(cast<CastInst>(I)->getSrcTy(), VF);
1468 Type *DestTy = ToVectorTy(cast<CastInst>(I)->getDestTy(), VF);
1469
1470 // If the truncate is free for the given types, return false. Replacing a
1471 // free truncate with an induction variable would add an induction variable
1472 // update instruction to each iteration of the loop. We exclude from this
1473 // check the primary induction variable since it will need an update
1474 // instruction regardless.
1475 Value *Op = Trunc->getOperand(0);
1476 if (Op != Legal->getPrimaryInduction() && TTI.isTruncateFree(SrcTy, DestTy))
1477 return false;
1478
1479 // If the truncated value is not an induction variable, return false.
1480 return Legal->isInductionPhi(Op);
1481 }
1482
1483 /// Collects the instructions to scalarize for each predicated instruction in
1484 /// the loop.
1485 void collectInstsToScalarize(ElementCount VF);
1486
1487 /// Collect Uniform and Scalar values for the given \p VF.
1488 /// The sets depend on CM decision for Load/Store instructions
1489 /// that may be vectorized as interleave, gather-scatter or scalarized.
1490 void collectUniformsAndScalars(ElementCount VF) {
1491 // Do the analysis once.
1492 if (VF.isScalar() || Uniforms.find(VF) != Uniforms.end())
1493 return;
1494 setCostBasedWideningDecision(VF);
1495 collectLoopUniforms(VF);
1496 collectLoopScalars(VF);
1497 }
1498
1499 /// Returns true if the target machine supports masked store operation
1500 /// for the given \p DataType and kind of access to \p Ptr.
1501 bool isLegalMaskedStore(Type *DataType, Value *Ptr, Align Alignment) const {
1502 return Legal->isConsecutivePtr(DataType, Ptr) &&
1503 TTI.isLegalMaskedStore(DataType, Alignment);
1504 }
1505
1506 /// Returns true if the target machine supports masked load operation
1507 /// for the given \p DataType and kind of access to \p Ptr.
1508 bool isLegalMaskedLoad(Type *DataType, Value *Ptr, Align Alignment) const {
1509 return Legal->isConsecutivePtr(DataType, Ptr) &&
1510 TTI.isLegalMaskedLoad(DataType, Alignment);
1511 }
1512
1513 /// Returns true if the target machine can represent \p V as a masked gather
1514 /// or scatter operation.
1515 bool isLegalGatherOrScatter(Value *V,
1516 ElementCount VF = ElementCount::getFixed(1)) {
1517 bool LI = isa<LoadInst>(V);
1518 bool SI = isa<StoreInst>(V);
1519 if (!LI && !SI)
1520 return false;
1521 auto *Ty = getLoadStoreType(V);
1522 Align Align = getLoadStoreAlignment(V);
1523 if (VF.isVector())
1524 Ty = VectorType::get(Ty, VF);
1525 return (LI && TTI.isLegalMaskedGather(Ty, Align)) ||
1526 (SI && TTI.isLegalMaskedScatter(Ty, Align));
1527 }
1528
1529 /// Returns true if the target machine supports all of the reduction
1530 /// variables found for the given VF.
1531 bool canVectorizeReductions(ElementCount VF) const {
1532 return (all_of(Legal->getReductionVars(), [&](auto &Reduction) -> bool {
1533 const RecurrenceDescriptor &RdxDesc = Reduction.second;
1534 return TTI.isLegalToVectorizeReduction(RdxDesc, VF);
1535 }));
1536 }
1537
1538 /// Returns true if \p I is an instruction that will be scalarized with
1539 /// predication when vectorizing \p I with vectorization factor \p VF. Such
1540 /// instructions include conditional stores and instructions that may divide
1541 /// by zero.
1542 bool isScalarWithPredication(Instruction *I, ElementCount VF) const;
1543
1544 // Returns true if \p I is an instruction that will be predicated either
1545 // through scalar predication or masked load/store or masked gather/scatter.
1546 // \p VF is the vectorization factor that will be used to vectorize \p I.
1547 // Superset of instructions that return true for isScalarWithPredication.
1548 bool isPredicatedInst(Instruction *I, ElementCount VF,
1549 bool IsKnownUniform = false) {
1550 // When we know the load is uniform and the original scalar loop was not
1551 // predicated we don't need to mark it as a predicated instruction. Any
1552 // vectorised blocks created when tail-folding are something artificial we
1553 // have introduced and we know there is always at least one active lane.
1554 // That's why we call Legal->blockNeedsPredication here because it doesn't
1555 // query tail-folding.
1556 if (IsKnownUniform && isa<LoadInst>(I) &&
1557 !Legal->blockNeedsPredication(I->getParent()))
1558 return false;
1559 if (!blockNeedsPredicationForAnyReason(I->getParent()))
1560 return false;
1561 // Loads and stores that need some form of masked operation are predicated
1562 // instructions.
1563 if (isa<LoadInst>(I) || isa<StoreInst>(I))
1564 return Legal->isMaskRequired(I);
1565 return isScalarWithPredication(I, VF);
1566 }
1567
1568 /// Returns true if \p I is a memory instruction with consecutive memory
1569 /// access that can be widened.
1570 bool
1571 memoryInstructionCanBeWidened(Instruction *I,
1572 ElementCount VF = ElementCount::getFixed(1));
1573
1574 /// Returns true if \p I is a memory instruction in an interleaved-group
1575 /// of memory accesses that can be vectorized with wide vector loads/stores
1576 /// and shuffles.
1577 bool
1578 interleavedAccessCanBeWidened(Instruction *I,
1579 ElementCount VF = ElementCount::getFixed(1));
1580
1581 /// Check if \p Instr belongs to any interleaved access group.
1582 bool isAccessInterleaved(Instruction *Instr) {
1583 return InterleaveInfo.isInterleaved(Instr);
1584 }
1585
1586 /// Get the interleaved access group that \p Instr belongs to.
1587 const InterleaveGroup<Instruction> *
1588 getInterleavedAccessGroup(Instruction *Instr) {
1589 return InterleaveInfo.getInterleaveGroup(Instr);
1590 }
1591
1592 /// Returns true if we're required to use a scalar epilogue for at least
1593 /// the final iteration of the original loop.
1594 bool requiresScalarEpilogue(ElementCount VF) const {
1595 if (!isScalarEpilogueAllowed())
1596 return false;
1597 // If we might exit from anywhere but the latch, must run the exiting
1598 // iteration in scalar form.
1599 if (TheLoop->getExitingBlock() != TheLoop->getLoopLatch())
1600 return true;
1601 return VF.isVector() && InterleaveInfo.requiresScalarEpilogue();
1602 }
1603
1604 /// Returns true if a scalar epilogue is not allowed due to optsize or a
1605 /// loop hint annotation.
1606 bool isScalarEpilogueAllowed() const {
1607 return ScalarEpilogueStatus == CM_ScalarEpilogueAllowed;
1608 }
1609
1610 /// Returns true if all loop blocks should be masked to fold tail loop.
1611 bool foldTailByMasking() const { return FoldTailByMasking; }
1612
1613 /// Returns true if the instructions in this block requires predication
1614 /// for any reason, e.g. because tail folding now requires a predicate
1615 /// or because the block in the original loop was predicated.
1616 bool blockNeedsPredicationForAnyReason(BasicBlock *BB) const {
1617 return foldTailByMasking() || Legal->blockNeedsPredication(BB);
1618 }
1619
1620 /// A SmallMapVector to store the InLoop reduction op chains, mapping phi
1621 /// nodes to the chain of instructions representing the reductions. Uses a
1622 /// MapVector to ensure deterministic iteration order.
1623 using ReductionChainMap =
1624 SmallMapVector<PHINode *, SmallVector<Instruction *, 4>, 4>;
1625
1626 /// Return the chain of instructions representing an inloop reduction.
1627 const ReductionChainMap &getInLoopReductionChains() const {
1628 return InLoopReductionChains;
1629 }
1630
1631 /// Returns true if the Phi is part of an inloop reduction.
1632 bool isInLoopReduction(PHINode *Phi) const {
1633 return InLoopReductionChains.count(Phi);
1634 }
1635
1636 /// Estimate cost of an intrinsic call instruction CI if it were vectorized
1637 /// with factor VF. Return the cost of the instruction, including
1638 /// scalarization overhead if it's needed.
1639 InstructionCost getVectorIntrinsicCost(CallInst *CI, ElementCount VF) const;
1640
1641 /// Estimate cost of a call instruction CI if it were vectorized with factor
1642 /// VF. Return the cost of the instruction, including scalarization overhead
1643 /// if it's needed. The flag NeedToScalarize shows if the call needs to be
1644 /// scalarized -
1645 /// i.e. either vector version isn't available, or is too expensive.
1646 InstructionCost getVectorCallCost(CallInst *CI, ElementCount VF,
1647 bool &NeedToScalarize) const;
1648
1649 /// Returns true if the per-lane cost of VectorizationFactor A is lower than
1650 /// that of B.
1651 bool isMoreProfitable(const VectorizationFactor &A,
1652 const VectorizationFactor &B) const;
1653
1654 /// Invalidates decisions already taken by the cost model.
1655 void invalidateCostModelingDecisions() {
1656 WideningDecisions.clear();
1657 Uniforms.clear();
1658 Scalars.clear();
1659 }
1660
1661private:
1662 unsigned NumPredStores = 0;
1663
1664 /// Convenience function that returns the value of vscale_range iff
1665 /// vscale_range.min == vscale_range.max or otherwise returns the value
1666 /// returned by the corresponding TLI method.
1667 Optional<unsigned> getVScaleForTuning() const;
1668
1669 /// \return An upper bound for the vectorization factors for both
1670 /// fixed and scalable vectorization, where the minimum-known number of
1671 /// elements is a power-of-2 larger than zero. If scalable vectorization is
1672 /// disabled or unsupported, then the scalable part will be equal to
1673 /// ElementCount::getScalable(0).
1674 FixedScalableVFPair computeFeasibleMaxVF(unsigned ConstTripCount,
1675 ElementCount UserVF,
1676 bool FoldTailByMasking);
1677
1678 /// \return the maximized element count based on the targets vector
1679 /// registers and the loop trip-count, but limited to a maximum safe VF.
1680 /// This is a helper function of computeFeasibleMaxVF.
1681 /// FIXME: MaxSafeVF is currently passed by reference to avoid some obscure
1682 /// issue that occurred on one of the buildbots which cannot be reproduced
1683 /// without having access to the properietary compiler (see comments on
1684 /// D98509). The issue is currently under investigation and this workaround
1685 /// will be removed as soon as possible.
1686 ElementCount getMaximizedVFForTarget(unsigned ConstTripCount,
1687 unsigned SmallestType,
1688 unsigned WidestType,
1689 const ElementCount &MaxSafeVF,
1690 bool FoldTailByMasking);
1691
1692 /// \return the maximum legal scalable VF, based on the safe max number
1693 /// of elements.
1694 ElementCount getMaxLegalScalableVF(unsigned MaxSafeElements);
1695
1696 /// The vectorization cost is a combination of the cost itself and a boolean
1697 /// indicating whether any of the contributing operations will actually
1698 /// operate on vector values after type legalization in the backend. If this
1699 /// latter value is false, then all operations will be scalarized (i.e. no
1700 /// vectorization has actually taken place).
1701 using VectorizationCostTy = std::pair<InstructionCost, bool>;
1702
1703 /// Returns the expected execution cost. The unit of the cost does
1704 /// not matter because we use the 'cost' units to compare different
1705 /// vector widths. The cost that is returned is *not* normalized by
1706 /// the factor width. If \p Invalid is not nullptr, this function
1707 /// will add a pair(Instruction*, ElementCount) to \p Invalid for
1708 /// each instruction that has an Invalid cost for the given VF.
1709 using InstructionVFPair = std::pair<Instruction *, ElementCount>;
1710 VectorizationCostTy
1711 expectedCost(ElementCount VF,
1712 SmallVectorImpl<InstructionVFPair> *Invalid = nullptr);
1713
1714 /// Returns the execution time cost of an instruction for a given vector
1715 /// width. Vector width of one means scalar.
1716 VectorizationCostTy getInstructionCost(Instruction *I, ElementCount VF);
1717
1718 /// The cost-computation logic from getInstructionCost which provides
1719 /// the vector type as an output parameter.
1720 InstructionCost getInstructionCost(Instruction *I, ElementCount VF,
1721 Type *&VectorTy);
1722
1723 /// Return the cost of instructions in an inloop reduction pattern, if I is
1724 /// part of that pattern.
1725 Optional<InstructionCost>
1726 getReductionPatternCost(Instruction *I, ElementCount VF, Type *VectorTy,
1727 TTI::TargetCostKind CostKind);
1728
1729 /// Calculate vectorization cost of memory instruction \p I.
1730 InstructionCost getMemoryInstructionCost(Instruction *I, ElementCount VF);
1731
1732 /// The cost computation for scalarized memory instruction.
1733 InstructionCost getMemInstScalarizationCost(Instruction *I, ElementCount VF);
1734
1735 /// The cost computation for interleaving group of memory instructions.
1736 InstructionCost getInterleaveGroupCost(Instruction *I, ElementCount VF);
1737
1738 /// The cost computation for Gather/Scatter instruction.
1739 InstructionCost getGatherScatterCost(Instruction *I, ElementCount VF);
1740
1741 /// The cost computation for widening instruction \p I with consecutive
1742 /// memory access.
1743 InstructionCost getConsecutiveMemOpCost(Instruction *I, ElementCount VF);
1744
1745 /// The cost calculation for Load/Store instruction \p I with uniform pointer -
1746 /// Load: scalar load + broadcast.
1747 /// Store: scalar store + (loop invariant value stored? 0 : extract of last
1748 /// element)
1749 InstructionCost getUniformMemOpCost(Instruction *I, ElementCount VF);
1750
1751 /// Estimate the overhead of scalarizing an instruction. This is a
1752 /// convenience wrapper for the type-based getScalarizationOverhead API.
1753 InstructionCost getScalarizationOverhead(Instruction *I,
1754 ElementCount VF) const;
1755
1756 /// Returns whether the instruction is a load or store and will be a emitted
1757 /// as a vector operation.
1758 bool isConsecutiveLoadOrStore(Instruction *I);
1759
1760 /// Returns true if an artificially high cost for emulated masked memrefs
1761 /// should be used.
1762 bool useEmulatedMaskMemRefHack(Instruction *I, ElementCount VF);
1763
1764 /// Map of scalar integer values to the smallest bitwidth they can be legally
1765 /// represented as. The vector equivalents of these values should be truncated
1766 /// to this type.
1767 MapVector<Instruction *, uint64_t> MinBWs;
1768
1769 /// A type representing the costs for instructions if they were to be
1770 /// scalarized rather than vectorized. The entries are Instruction-Cost
1771 /// pairs.
1772 using ScalarCostsTy = DenseMap<Instruction *, InstructionCost>;
1773
1774 /// A set containing all BasicBlocks that are known to present after
1775 /// vectorization as a predicated block.
1776 SmallPtrSet<BasicBlock *, 4> PredicatedBBsAfterVectorization;
1777
1778 /// Records whether it is allowed to have the original scalar loop execute at
1779 /// least once. This may be needed as a fallback loop in case runtime
1780 /// aliasing/dependence checks fail, or to handle the tail/remainder
1781 /// iterations when the trip count is unknown or doesn't divide by the VF,
1782 /// or as a peel-loop to handle gaps in interleave-groups.
1783 /// Under optsize and when the trip count is very small we don't allow any
1784 /// iterations to execute in the scalar loop.
1785 ScalarEpilogueLowering ScalarEpilogueStatus = CM_ScalarEpilogueAllowed;
1786
1787 /// All blocks of loop are to be masked to fold tail of scalar iterations.
1788 bool FoldTailByMasking = false;
1789
1790 /// A map holding scalar costs for different vectorization factors. The
1791 /// presence of a cost for an instruction in the mapping indicates that the
1792 /// instruction will be scalarized when vectorizing with the associated
1793 /// vectorization factor. The entries are VF-ScalarCostTy pairs.
1794 DenseMap<ElementCount, ScalarCostsTy> InstsToScalarize;
1795
1796 /// Holds the instructions known to be uniform after vectorization.
1797 /// The data is collected per VF.
1798 DenseMap<ElementCount, SmallPtrSet<Instruction *, 4>> Uniforms;
1799
1800 /// Holds the instructions known to be scalar after vectorization.
1801 /// The data is collected per VF.
1802 DenseMap<ElementCount, SmallPtrSet<Instruction *, 4>> Scalars;
1803
1804 /// Holds the instructions (address computations) that are forced to be
1805 /// scalarized.
1806 DenseMap<ElementCount, SmallPtrSet<Instruction *, 4>> ForcedScalars;
1807
1808 /// PHINodes of the reductions that should be expanded in-loop along with
1809 /// their associated chains of reduction operations, in program order from top
1810 /// (PHI) to bottom
1811 ReductionChainMap InLoopReductionChains;
1812
1813 /// A Map of inloop reduction operations and their immediate chain operand.
1814 /// FIXME: This can be removed once reductions can be costed correctly in
1815 /// vplan. This was added to allow quick lookup to the inloop operations,
1816 /// without having to loop through InLoopReductionChains.
1817 DenseMap<Instruction *, Instruction *> InLoopReductionImmediateChains;
1818
1819 /// Returns the expected difference in cost from scalarizing the expression
1820 /// feeding a predicated instruction \p PredInst. The instructions to
1821 /// scalarize and their scalar costs are collected in \p ScalarCosts. A
1822 /// non-negative return value implies the expression will be scalarized.
1823 /// Currently, only single-use chains are considered for scalarization.
1824 int computePredInstDiscount(Instruction *PredInst, ScalarCostsTy &ScalarCosts,
1825 ElementCount VF);
1826
1827 /// Collect the instructions that are uniform after vectorization. An
1828 /// instruction is uniform if we represent it with a single scalar value in
1829 /// the vectorized loop corresponding to each vector iteration. Examples of
1830 /// uniform instructions include pointer operands of consecutive or
1831 /// interleaved memory accesses. Note that although uniformity implies an
1832 /// instruction will be scalar, the reverse is not true. In general, a
1833 /// scalarized instruction will be represented by VF scalar values in the
1834 /// vectorized loop, each corresponding to an iteration of the original
1835 /// scalar loop.
1836 void collectLoopUniforms(ElementCount VF);
1837
1838 /// Collect the instructions that are scalar after vectorization. An
1839 /// instruction is scalar if it is known to be uniform or will be scalarized
1840 /// during vectorization. collectLoopScalars should only add non-uniform nodes
1841 /// to the list if they are used by a load/store instruction that is marked as
1842 /// CM_Scalarize. Non-uniform scalarized instructions will be represented by
1843 /// VF values in the vectorized loop, each corresponding to an iteration of
1844 /// the original scalar loop.
1845 void collectLoopScalars(ElementCount VF);
1846
1847 /// Keeps cost model vectorization decision and cost for instructions.
1848 /// Right now it is used for memory instructions only.
1849 using DecisionList = DenseMap<std::pair<Instruction *, ElementCount>,
1850 std::pair<InstWidening, InstructionCost>>;
1851
1852 DecisionList WideningDecisions;
1853
1854 /// Returns true if \p V is expected to be vectorized and it needs to be
1855 /// extracted.
1856 bool needsExtract(Value *V, ElementCount VF) const {
1857 Instruction *I = dyn_cast<Instruction>(V);
1858 if (VF.isScalar() || !I || !TheLoop->contains(I) ||
1859 TheLoop->isLoopInvariant(I))
1860 return false;
1861
1862 // Assume we can vectorize V (and hence we need extraction) if the
1863 // scalars are not computed yet. This can happen, because it is called
1864 // via getScalarizationOverhead from setCostBasedWideningDecision, before
1865 // the scalars are collected. That should be a safe assumption in most
1866 // cases, because we check if the operands have vectorizable types
1867 // beforehand in LoopVectorizationLegality.
1868 return Scalars.find(VF) == Scalars.end() ||
1869 !isScalarAfterVectorization(I, VF);
1870 };
1871
1872 /// Returns a range containing only operands needing to be extracted.
1873 SmallVector<Value *, 4> filterExtractingOperands(Instruction::op_range Ops,
1874 ElementCount VF) const {
1875 return SmallVector<Value *, 4>(make_filter_range(
1876 Ops, [this, VF](Value *V) { return this->needsExtract(V, VF); }));
1877 }
1878
1879 /// Determines if we have the infrastructure to vectorize loop \p L and its
1880 /// epilogue, assuming the main loop is vectorized by \p VF.
1881 bool isCandidateForEpilogueVectorization(const Loop &L,
1882 const ElementCount VF) const;
1883
1884 /// Returns true if epilogue vectorization is considered profitable, and
1885 /// false otherwise.
1886 /// \p VF is the vectorization factor chosen for the original loop.
1887 bool isEpilogueVectorizationProfitable(const ElementCount VF) const;
1888
1889public:
1890 /// The loop that we evaluate.
1891 Loop *TheLoop;
1892
1893 /// Predicated scalar evolution analysis.
1894 PredicatedScalarEvolution &PSE;
1895
1896 /// Loop Info analysis.
1897 LoopInfo *LI;
1898
1899 /// Vectorization legality.
1900 LoopVectorizationLegality *Legal;
1901
1902 /// Vector target information.
1903 const TargetTransformInfo &TTI;
1904
1905 /// Target Library Info.
1906 const TargetLibraryInfo *TLI;
1907
1908 /// Demanded bits analysis.
1909 DemandedBits *DB;
1910
1911 /// Assumption cache.
1912 AssumptionCache *AC;
1913
1914 /// Interface to emit optimization remarks.
1915 OptimizationRemarkEmitter *ORE;
1916
1917 const Function *TheFunction;
1918
1919 /// Loop Vectorize Hint.
1920 const LoopVectorizeHints *Hints;
1921
1922 /// The interleave access information contains groups of interleaved accesses
1923 /// with the same stride and close to each other.
1924 InterleavedAccessInfo &InterleaveInfo;
1925
1926 /// Values to ignore in the cost model.
1927 SmallPtrSet<const Value *, 16> ValuesToIgnore;
1928
1929 /// Values to ignore in the cost model when VF > 1.
1930 SmallPtrSet<const Value *, 16> VecValuesToIgnore;
1931
1932 /// All element types found in the loop.
1933 SmallPtrSet<Type *, 16> ElementTypesInLoop;
1934
1935 /// Profitable vector factors.
1936 SmallVector<VectorizationFactor, 8> ProfitableVFs;
1937};
1938} // end namespace llvm
1939
1940/// Helper struct to manage generating runtime checks for vectorization.
1941///
1942/// The runtime checks are created up-front in temporary blocks to allow better
1943/// estimating the cost and un-linked from the existing IR. After deciding to
1944/// vectorize, the checks are moved back. If deciding not to vectorize, the
1945/// temporary blocks are completely removed.
1946class GeneratedRTChecks {
1947 /// Basic block which contains the generated SCEV checks, if any.
1948 BasicBlock *SCEVCheckBlock = nullptr;
1949
1950 /// The value representing the result of the generated SCEV checks. If it is
1951 /// nullptr, either no SCEV checks have been generated or they have been used.
1952 Value *SCEVCheckCond = nullptr;
1953
1954 /// Basic block which contains the generated memory runtime checks, if any.
1955 BasicBlock *MemCheckBlock = nullptr;
1956
1957 /// The value representing the result of the generated memory runtime checks.
1958 /// If it is nullptr, either no memory runtime checks have been generated or
1959 /// they have been used.
1960 Value *MemRuntimeCheckCond = nullptr;
1961
1962 DominatorTree *DT;
1963 LoopInfo *LI;
1964
1965 SCEVExpander SCEVExp;
1966 SCEVExpander MemCheckExp;
1967
1968public:
1969 GeneratedRTChecks(ScalarEvolution &SE, DominatorTree *DT, LoopInfo *LI,
1970 const DataLayout &DL)
1971 : DT(DT), LI(LI), SCEVExp(SE, DL, "scev.check"),
1972 MemCheckExp(SE, DL, "scev.check") {}
1973
1974 /// Generate runtime checks in SCEVCheckBlock and MemCheckBlock, so we can
1975 /// accurately estimate the cost of the runtime checks. The blocks are
1976 /// un-linked from the IR and is added back during vector code generation. If
1977 /// there is no vector code generation, the check blocks are removed
1978 /// completely.
1979 void Create(Loop *L, const LoopAccessInfo &LAI,
1980 const SCEVPredicate &Pred) {
1981
1982 BasicBlock *LoopHeader = L->getHeader();
1983 BasicBlock *Preheader = L->getLoopPreheader();
1984
1985 // Use SplitBlock to create blocks for SCEV & memory runtime checks to
1986 // ensure the blocks are properly added to LoopInfo & DominatorTree. Those
1987 // may be used by SCEVExpander. The blocks will be un-linked from their
1988 // predecessors and removed from LI & DT at the end of the function.
1989 if (!Pred.isAlwaysTrue()) {
1990 SCEVCheckBlock = SplitBlock(Preheader, Preheader->getTerminator(), DT, LI,
1991 nullptr, "vector.scevcheck");
1992
1993 SCEVCheckCond = SCEVExp.expandCodeForPredicate(
1994 &Pred, SCEVCheckBlock->getTerminator());
1995 }
1996
1997 const auto &RtPtrChecking = *LAI.getRuntimePointerChecking();
1998 if (RtPtrChecking.Need) {
1999 auto *Pred = SCEVCheckBlock ? SCEVCheckBlock : Preheader;
2000 MemCheckBlock = SplitBlock(Pred, Pred->getTerminator(), DT, LI, nullptr,
2001 "vector.memcheck");
2002
2003 MemRuntimeCheckCond =
2004 addRuntimeChecks(MemCheckBlock->getTerminator(), L,
2005 RtPtrChecking.getChecks(), MemCheckExp);
2006 assert(MemRuntimeCheckCond &&(static_cast <bool> (MemRuntimeCheckCond && "no RT checks generated although RtPtrChecking "
"claimed checks are required") ? void (0) : __assert_fail ("MemRuntimeCheckCond && \"no RT checks generated although RtPtrChecking \" \"claimed checks are required\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2008, __extension__
__PRETTY_FUNCTION__))
2007 "no RT checks generated although RtPtrChecking "(static_cast <bool> (MemRuntimeCheckCond && "no RT checks generated although RtPtrChecking "
"claimed checks are required") ? void (0) : __assert_fail ("MemRuntimeCheckCond && \"no RT checks generated although RtPtrChecking \" \"claimed checks are required\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2008, __extension__
__PRETTY_FUNCTION__))
2008 "claimed checks are required")(static_cast <bool> (MemRuntimeCheckCond && "no RT checks generated although RtPtrChecking "
"claimed checks are required") ? void (0) : __assert_fail ("MemRuntimeCheckCond && \"no RT checks generated although RtPtrChecking \" \"claimed checks are required\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2008, __extension__
__PRETTY_FUNCTION__))
;
2009 }
2010
2011 if (!MemCheckBlock && !SCEVCheckBlock)
2012 return;
2013
2014 // Unhook the temporary block with the checks, update various places
2015 // accordingly.
2016 if (SCEVCheckBlock)
2017 SCEVCheckBlock->replaceAllUsesWith(Preheader);
2018 if (MemCheckBlock)
2019 MemCheckBlock->replaceAllUsesWith(Preheader);
2020
2021 if (SCEVCheckBlock) {
2022 SCEVCheckBlock->getTerminator()->moveBefore(Preheader->getTerminator());
2023 new UnreachableInst(Preheader->getContext(), SCEVCheckBlock);
2024 Preheader->getTerminator()->eraseFromParent();
2025 }
2026 if (MemCheckBlock) {
2027 MemCheckBlock->getTerminator()->moveBefore(Preheader->getTerminator());
2028 new UnreachableInst(Preheader->getContext(), MemCheckBlock);
2029 Preheader->getTerminator()->eraseFromParent();
2030 }
2031
2032 DT->changeImmediateDominator(LoopHeader, Preheader);
2033 if (MemCheckBlock) {
2034 DT->eraseNode(MemCheckBlock);
2035 LI->removeBlock(MemCheckBlock);
2036 }
2037 if (SCEVCheckBlock) {
2038 DT->eraseNode(SCEVCheckBlock);
2039 LI->removeBlock(SCEVCheckBlock);
2040 }
2041 }
2042
2043 /// Remove the created SCEV & memory runtime check blocks & instructions, if
2044 /// unused.
2045 ~GeneratedRTChecks() {
2046 SCEVExpanderCleaner SCEVCleaner(SCEVExp);
2047 SCEVExpanderCleaner MemCheckCleaner(MemCheckExp);
2048 if (!SCEVCheckCond)
2049 SCEVCleaner.markResultUsed();
2050
2051 if (!MemRuntimeCheckCond)
2052 MemCheckCleaner.markResultUsed();
2053
2054 if (MemRuntimeCheckCond) {
2055 auto &SE = *MemCheckExp.getSE();
2056 // Memory runtime check generation creates compares that use expanded
2057 // values. Remove them before running the SCEVExpanderCleaners.
2058 for (auto &I : make_early_inc_range(reverse(*MemCheckBlock))) {
2059 if (MemCheckExp.isInsertedInstruction(&I))
2060 continue;
2061 SE.forgetValue(&I);
2062 I.eraseFromParent();
2063 }
2064 }
2065 MemCheckCleaner.cleanup();
2066 SCEVCleaner.cleanup();
2067
2068 if (SCEVCheckCond)
2069 SCEVCheckBlock->eraseFromParent();
2070 if (MemRuntimeCheckCond)
2071 MemCheckBlock->eraseFromParent();
2072 }
2073
2074 /// Adds the generated SCEVCheckBlock before \p LoopVectorPreHeader and
2075 /// adjusts the branches to branch to the vector preheader or \p Bypass,
2076 /// depending on the generated condition.
2077 BasicBlock *emitSCEVChecks(BasicBlock *Bypass,
2078 BasicBlock *LoopVectorPreHeader,
2079 BasicBlock *LoopExitBlock) {
2080 if (!SCEVCheckCond)
2081 return nullptr;
2082 if (auto *C = dyn_cast<ConstantInt>(SCEVCheckCond))
2083 if (C->isZero())
2084 return nullptr;
2085
2086 auto *Pred = LoopVectorPreHeader->getSinglePredecessor();
2087
2088 BranchInst::Create(LoopVectorPreHeader, SCEVCheckBlock);
2089 // Create new preheader for vector loop.
2090 if (auto *PL = LI->getLoopFor(LoopVectorPreHeader))
2091 PL->addBasicBlockToLoop(SCEVCheckBlock, *LI);
2092
2093 SCEVCheckBlock->getTerminator()->eraseFromParent();
2094 SCEVCheckBlock->moveBefore(LoopVectorPreHeader);
2095 Pred->getTerminator()->replaceSuccessorWith(LoopVectorPreHeader,
2096 SCEVCheckBlock);
2097
2098 DT->addNewBlock(SCEVCheckBlock, Pred);
2099 DT->changeImmediateDominator(LoopVectorPreHeader, SCEVCheckBlock);
2100
2101 ReplaceInstWithInst(
2102 SCEVCheckBlock->getTerminator(),
2103 BranchInst::Create(Bypass, LoopVectorPreHeader, SCEVCheckCond));
2104 // Mark the check as used, to prevent it from being removed during cleanup.
2105 SCEVCheckCond = nullptr;
2106 return SCEVCheckBlock;
2107 }
2108
2109 /// Adds the generated MemCheckBlock before \p LoopVectorPreHeader and adjusts
2110 /// the branches to branch to the vector preheader or \p Bypass, depending on
2111 /// the generated condition.
2112 BasicBlock *emitMemRuntimeChecks(Loop *L, BasicBlock *Bypass,
2113 BasicBlock *LoopVectorPreHeader) {
2114 // Check if we generated code that checks in runtime if arrays overlap.
2115 if (!MemRuntimeCheckCond)
2116 return nullptr;
2117
2118 auto *Pred = LoopVectorPreHeader->getSinglePredecessor();
2119 Pred->getTerminator()->replaceSuccessorWith(LoopVectorPreHeader,
2120 MemCheckBlock);
2121
2122 DT->addNewBlock(MemCheckBlock, Pred);
2123 DT->changeImmediateDominator(LoopVectorPreHeader, MemCheckBlock);
2124 MemCheckBlock->moveBefore(LoopVectorPreHeader);
2125
2126 if (auto *PL = LI->getLoopFor(LoopVectorPreHeader))
2127 PL->addBasicBlockToLoop(MemCheckBlock, *LI);
2128
2129 ReplaceInstWithInst(
2130 MemCheckBlock->getTerminator(),
2131 BranchInst::Create(Bypass, LoopVectorPreHeader, MemRuntimeCheckCond));
2132 MemCheckBlock->getTerminator()->setDebugLoc(
2133 Pred->getTerminator()->getDebugLoc());
2134
2135 // Mark the check as used, to prevent it from being removed during cleanup.
2136 MemRuntimeCheckCond = nullptr;
2137 return MemCheckBlock;
2138 }
2139};
2140
2141// Return true if \p OuterLp is an outer loop annotated with hints for explicit
2142// vectorization. The loop needs to be annotated with #pragma omp simd
2143// simdlen(#) or #pragma clang vectorize(enable) vectorize_width(#). If the
2144// vector length information is not provided, vectorization is not considered
2145// explicit. Interleave hints are not allowed either. These limitations will be
2146// relaxed in the future.
2147// Please, note that we are currently forced to abuse the pragma 'clang
2148// vectorize' semantics. This pragma provides *auto-vectorization hints*
2149// (i.e., LV must check that vectorization is legal) whereas pragma 'omp simd'
2150// provides *explicit vectorization hints* (LV can bypass legal checks and
2151// assume that vectorization is legal). However, both hints are implemented
2152// using the same metadata (llvm.loop.vectorize, processed by
2153// LoopVectorizeHints). This will be fixed in the future when the native IR
2154// representation for pragma 'omp simd' is introduced.
2155static bool isExplicitVecOuterLoop(Loop *OuterLp,
2156 OptimizationRemarkEmitter *ORE) {
2157 assert(!OuterLp->isInnermost() && "This is not an outer loop")(static_cast <bool> (!OuterLp->isInnermost() &&
"This is not an outer loop") ? void (0) : __assert_fail ("!OuterLp->isInnermost() && \"This is not an outer loop\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2157, __extension__
__PRETTY_FUNCTION__))
;
2158 LoopVectorizeHints Hints(OuterLp, true /*DisableInterleaving*/, *ORE);
2159
2160 // Only outer loops with an explicit vectorization hint are supported.
2161 // Unannotated outer loops are ignored.
2162 if (Hints.getForce() == LoopVectorizeHints::FK_Undefined)
2163 return false;
2164
2165 Function *Fn = OuterLp->getHeader()->getParent();
2166 if (!Hints.allowVectorization(Fn, OuterLp,
2167 true /*VectorizeOnlyWhenForced*/)) {
2168 LLVM_DEBUG(dbgs() << "LV: Loop hints prevent outer loop vectorization.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints prevent outer loop vectorization.\n"
; } } while (false)
;
2169 return false;
2170 }
2171
2172 if (Hints.getInterleave() > 1) {
2173 // TODO: Interleave support is future work.
2174 LLVM_DEBUG(dbgs() << "LV: Not vectorizing: Interleave is not supported for "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not vectorizing: Interleave is not supported for "
"outer loops.\n"; } } while (false)
2175 "outer loops.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not vectorizing: Interleave is not supported for "
"outer loops.\n"; } } while (false)
;
2176 Hints.emitRemarkWithHints();
2177 return false;
2178 }
2179
2180 return true;
2181}
2182
2183static void collectSupportedLoops(Loop &L, LoopInfo *LI,
2184 OptimizationRemarkEmitter *ORE,
2185 SmallVectorImpl<Loop *> &V) {
2186 // Collect inner loops and outer loops without irreducible control flow. For
2187 // now, only collect outer loops that have explicit vectorization hints. If we
2188 // are stress testing the VPlan H-CFG construction, we collect the outermost
2189 // loop of every loop nest.
2190 if (L.isInnermost() || VPlanBuildStressTest ||
2191 (EnableVPlanNativePath && isExplicitVecOuterLoop(&L, ORE))) {
2192 LoopBlocksRPO RPOT(&L);
2193 RPOT.perform(LI);
2194 if (!containsIrreducibleCFG<const BasicBlock *>(RPOT, *LI)) {
2195 V.push_back(&L);
2196 // TODO: Collect inner loops inside marked outer loops in case
2197 // vectorization fails for the outer loop. Do not invoke
2198 // 'containsIrreducibleCFG' again for inner loops when the outer loop is
2199 // already known to be reducible. We can use an inherited attribute for
2200 // that.
2201 return;
2202 }
2203 }
2204 for (Loop *InnerL : L)
2205 collectSupportedLoops(*InnerL, LI, ORE, V);
2206}
2207
2208namespace {
2209
2210/// The LoopVectorize Pass.
2211struct LoopVectorize : public FunctionPass {
2212 /// Pass identification, replacement for typeid
2213 static char ID;
2214
2215 LoopVectorizePass Impl;
2216
2217 explicit LoopVectorize(bool InterleaveOnlyWhenForced = false,
2218 bool VectorizeOnlyWhenForced = false)
2219 : FunctionPass(ID),
2220 Impl({InterleaveOnlyWhenForced, VectorizeOnlyWhenForced}) {
2221 initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
2222 }
2223
2224 bool runOnFunction(Function &F) override {
2225 if (skipFunction(F))
2226 return false;
2227
2228 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
2229 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
2230 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
2231 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
2232 auto *BFI = &getAnalysis<BlockFrequencyInfoWrapperPass>().getBFI();
2233 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>();
2234 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr;
2235 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults();
2236 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
2237 auto *LAA = &getAnalysis<LoopAccessLegacyAnalysis>();
2238 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits();
2239 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE();
2240 auto *PSI = &getAnalysis<ProfileSummaryInfoWrapperPass>().getPSI();
2241
2242 std::function<const LoopAccessInfo &(Loop &)> GetLAA =
2243 [&](Loop &L) -> const LoopAccessInfo & { return LAA->getInfo(&L); };
2244
2245 return Impl.runImpl(F, *SE, *LI, *TTI, *DT, *BFI, TLI, *DB, *AA, *AC,
2246 GetLAA, *ORE, PSI).MadeAnyChange;
2247 }
2248
2249 void getAnalysisUsage(AnalysisUsage &AU) const override {
2250 AU.addRequired<AssumptionCacheTracker>();
2251 AU.addRequired<BlockFrequencyInfoWrapperPass>();
2252 AU.addRequired<DominatorTreeWrapperPass>();
2253 AU.addRequired<LoopInfoWrapperPass>();
2254 AU.addRequired<ScalarEvolutionWrapperPass>();
2255 AU.addRequired<TargetTransformInfoWrapperPass>();
2256 AU.addRequired<AAResultsWrapperPass>();
2257 AU.addRequired<LoopAccessLegacyAnalysis>();
2258 AU.addRequired<DemandedBitsWrapperPass>();
2259 AU.addRequired<OptimizationRemarkEmitterWrapperPass>();
2260 AU.addRequired<InjectTLIMappingsLegacy>();
2261
2262 // We currently do not preserve loopinfo/dominator analyses with outer loop
2263 // vectorization. Until this is addressed, mark these analyses as preserved
2264 // only for non-VPlan-native path.
2265 // TODO: Preserve Loop and Dominator analyses for VPlan-native path.
2266 if (!EnableVPlanNativePath) {
2267 AU.addPreserved<LoopInfoWrapperPass>();
2268 AU.addPreserved<DominatorTreeWrapperPass>();
2269 }
2270
2271 AU.addPreserved<BasicAAWrapperPass>();
2272 AU.addPreserved<GlobalsAAWrapperPass>();
2273 AU.addRequired<ProfileSummaryInfoWrapperPass>();
2274 }
2275};
2276
2277} // end anonymous namespace
2278
2279//===----------------------------------------------------------------------===//
2280// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
2281// LoopVectorizationCostModel and LoopVectorizationPlanner.
2282//===----------------------------------------------------------------------===//
2283
2284Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
2285 // We need to place the broadcast of invariant variables outside the loop,
2286 // but only if it's proven safe to do so. Else, broadcast will be inside
2287 // vector loop body.
2288 Instruction *Instr = dyn_cast<Instruction>(V);
2289 bool SafeToHoist = OrigLoop->isLoopInvariant(V) &&
2290 (!Instr ||
2291 DT->dominates(Instr->getParent(), LoopVectorPreHeader));
2292 // Place the code for broadcasting invariant variables in the new preheader.
2293 IRBuilder<>::InsertPointGuard Guard(Builder);
2294 if (SafeToHoist)
2295 Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
2296
2297 // Broadcast the scalar into all locations in the vector.
2298 Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
2299
2300 return Shuf;
2301}
2302
2303/// This function adds
2304/// (StartIdx * Step, (StartIdx + 1) * Step, (StartIdx + 2) * Step, ...)
2305/// to each vector element of Val. The sequence starts at StartIndex.
2306/// \p Opcode is relevant for FP induction variable.
2307static Value *getStepVector(Value *Val, Value *StartIdx, Value *Step,
2308 Instruction::BinaryOps BinOp, ElementCount VF,
2309 IRBuilderBase &Builder) {
2310 assert(VF.isVector() && "only vector VFs are supported")(static_cast <bool> (VF.isVector() && "only vector VFs are supported"
) ? void (0) : __assert_fail ("VF.isVector() && \"only vector VFs are supported\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2310, __extension__
__PRETTY_FUNCTION__))
;
2311
2312 // Create and check the types.
2313 auto *ValVTy = cast<VectorType>(Val->getType());
2314 ElementCount VLen = ValVTy->getElementCount();
2315
2316 Type *STy = Val->getType()->getScalarType();
2317 assert((STy->isIntegerTy() || STy->isFloatingPointTy()) &&(static_cast <bool> ((STy->isIntegerTy() || STy->
isFloatingPointTy()) && "Induction Step must be an integer or FP"
) ? void (0) : __assert_fail ("(STy->isIntegerTy() || STy->isFloatingPointTy()) && \"Induction Step must be an integer or FP\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2318, __extension__
__PRETTY_FUNCTION__))
2318 "Induction Step must be an integer or FP")(static_cast <bool> ((STy->isIntegerTy() || STy->
isFloatingPointTy()) && "Induction Step must be an integer or FP"
) ? void (0) : __assert_fail ("(STy->isIntegerTy() || STy->isFloatingPointTy()) && \"Induction Step must be an integer or FP\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2318, __extension__
__PRETTY_FUNCTION__))
;
2319 assert(Step->getType() == STy && "Step has wrong type")(static_cast <bool> (Step->getType() == STy &&
"Step has wrong type") ? void (0) : __assert_fail ("Step->getType() == STy && \"Step has wrong type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2319, __extension__
__PRETTY_FUNCTION__))
;
2320
2321 SmallVector<Constant *, 8> Indices;
2322
2323 // Create a vector of consecutive numbers from zero to VF.
2324 VectorType *InitVecValVTy = ValVTy;
2325 if (STy->isFloatingPointTy()) {
2326 Type *InitVecValSTy =
2327 IntegerType::get(STy->getContext(), STy->getScalarSizeInBits());
2328 InitVecValVTy = VectorType::get(InitVecValSTy, VLen);
2329 }
2330 Value *InitVec = Builder.CreateStepVector(InitVecValVTy);
2331
2332 // Splat the StartIdx
2333 Value *StartIdxSplat = Builder.CreateVectorSplat(VLen, StartIdx);
2334
2335 if (STy->isIntegerTy()) {
2336 InitVec = Builder.CreateAdd(InitVec, StartIdxSplat);
2337 Step = Builder.CreateVectorSplat(VLen, Step);
2338 assert(Step->getType() == Val->getType() && "Invalid step vec")(static_cast <bool> (Step->getType() == Val->getType
() && "Invalid step vec") ? void (0) : __assert_fail (
"Step->getType() == Val->getType() && \"Invalid step vec\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2338, __extension__
__PRETTY_FUNCTION__))
;
2339 // FIXME: The newly created binary instructions should contain nsw/nuw
2340 // flags, which can be found from the original scalar operations.
2341 Step = Builder.CreateMul(InitVec, Step);
2342 return Builder.CreateAdd(Val, Step, "induction");
2343 }
2344
2345 // Floating point induction.
2346 assert((BinOp == Instruction::FAdd || BinOp == Instruction::FSub) &&(static_cast <bool> ((BinOp == Instruction::FAdd || BinOp
== Instruction::FSub) && "Binary Opcode should be specified for FP induction"
) ? void (0) : __assert_fail ("(BinOp == Instruction::FAdd || BinOp == Instruction::FSub) && \"Binary Opcode should be specified for FP induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2347, __extension__
__PRETTY_FUNCTION__))
2347 "Binary Opcode should be specified for FP induction")(static_cast <bool> ((BinOp == Instruction::FAdd || BinOp
== Instruction::FSub) && "Binary Opcode should be specified for FP induction"
) ? void (0) : __assert_fail ("(BinOp == Instruction::FAdd || BinOp == Instruction::FSub) && \"Binary Opcode should be specified for FP induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2347, __extension__
__PRETTY_FUNCTION__))
;
2348 InitVec = Builder.CreateUIToFP(InitVec, ValVTy);
2349 InitVec = Builder.CreateFAdd(InitVec, StartIdxSplat);
2350
2351 Step = Builder.CreateVectorSplat(VLen, Step);
2352 Value *MulOp = Builder.CreateFMul(InitVec, Step);
2353 return Builder.CreateBinOp(BinOp, Val, MulOp, "induction");
2354}
2355
2356/// Compute scalar induction steps. \p ScalarIV is the scalar induction
2357/// variable on which to base the steps, \p Step is the size of the step.
2358static void buildScalarSteps(Value *ScalarIV, Value *Step,
2359 const InductionDescriptor &ID, VPValue *Def,
2360 VPTransformState &State) {
2361 IRBuilderBase &Builder = State.Builder;
2362 // We shouldn't have to build scalar steps if we aren't vectorizing.
2363 assert(State.VF.isVector() && "VF should be greater than one")(static_cast <bool> (State.VF.isVector() && "VF should be greater than one"
) ? void (0) : __assert_fail ("State.VF.isVector() && \"VF should be greater than one\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2363, __extension__
__PRETTY_FUNCTION__))
;
2364 // Get the value type and ensure it and the step have the same integer type.
2365 Type *ScalarIVTy = ScalarIV->getType()->getScalarType();
2366 assert(ScalarIVTy == Step->getType() &&(static_cast <bool> (ScalarIVTy == Step->getType() &&
"Val and Step should have the same type") ? void (0) : __assert_fail
("ScalarIVTy == Step->getType() && \"Val and Step should have the same type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2367, __extension__
__PRETTY_FUNCTION__))
2367 "Val and Step should have the same type")(static_cast <bool> (ScalarIVTy == Step->getType() &&
"Val and Step should have the same type") ? void (0) : __assert_fail
("ScalarIVTy == Step->getType() && \"Val and Step should have the same type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2367, __extension__
__PRETTY_FUNCTION__))
;
2368
2369 // We build scalar steps for both integer and floating-point induction
2370 // variables. Here, we determine the kind of arithmetic we will perform.
2371 Instruction::BinaryOps AddOp;
2372 Instruction::BinaryOps MulOp;
2373 if (ScalarIVTy->isIntegerTy()) {
2374 AddOp = Instruction::Add;
2375 MulOp = Instruction::Mul;
2376 } else {
2377 AddOp = ID.getInductionOpcode();
2378 MulOp = Instruction::FMul;
2379 }
2380
2381 // Determine the number of scalars we need to generate for each unroll
2382 // iteration.
2383 bool FirstLaneOnly = vputils::onlyFirstLaneUsed(Def);
2384 unsigned Lanes = FirstLaneOnly ? 1 : State.VF.getKnownMinValue();
2385 // Compute the scalar steps and save the results in State.
2386 Type *IntStepTy = IntegerType::get(ScalarIVTy->getContext(),
2387 ScalarIVTy->getScalarSizeInBits());
2388 Type *VecIVTy = nullptr;
2389 Value *UnitStepVec = nullptr, *SplatStep = nullptr, *SplatIV = nullptr;
2390 if (!FirstLaneOnly && State.VF.isScalable()) {
2391 VecIVTy = VectorType::get(ScalarIVTy, State.VF);
2392 UnitStepVec =
2393 Builder.CreateStepVector(VectorType::get(IntStepTy, State.VF));
2394 SplatStep = Builder.CreateVectorSplat(State.VF, Step);
2395 SplatIV = Builder.CreateVectorSplat(State.VF, ScalarIV);
2396 }
2397
2398 for (unsigned Part = 0; Part < State.UF; ++Part) {
2399 Value *StartIdx0 = createStepForVF(Builder, IntStepTy, State.VF, Part);
2400
2401 if (!FirstLaneOnly && State.VF.isScalable()) {
2402 auto *SplatStartIdx = Builder.CreateVectorSplat(State.VF, StartIdx0);
2403 auto *InitVec = Builder.CreateAdd(SplatStartIdx, UnitStepVec);
2404 if (ScalarIVTy->isFloatingPointTy())
2405 InitVec = Builder.CreateSIToFP(InitVec, VecIVTy);
2406 auto *Mul = Builder.CreateBinOp(MulOp, InitVec, SplatStep);
2407 auto *Add = Builder.CreateBinOp(AddOp, SplatIV, Mul);
2408 State.set(Def, Add, Part);
2409 // It's useful to record the lane values too for the known minimum number
2410 // of elements so we do those below. This improves the code quality when
2411 // trying to extract the first element, for example.
2412 }
2413
2414 if (ScalarIVTy->isFloatingPointTy())
2415 StartIdx0 = Builder.CreateSIToFP(StartIdx0, ScalarIVTy);
2416
2417 for (unsigned Lane = 0; Lane < Lanes; ++Lane) {
2418 Value *StartIdx = Builder.CreateBinOp(
2419 AddOp, StartIdx0, getSignedIntOrFpConstant(ScalarIVTy, Lane));
2420 // The step returned by `createStepForVF` is a runtime-evaluated value
2421 // when VF is scalable. Otherwise, it should be folded into a Constant.
2422 assert((State.VF.isScalable() || isa<Constant>(StartIdx)) &&(static_cast <bool> ((State.VF.isScalable() || isa<Constant
>(StartIdx)) && "Expected StartIdx to be folded to a constant when VF is not "
"scalable") ? void (0) : __assert_fail ("(State.VF.isScalable() || isa<Constant>(StartIdx)) && \"Expected StartIdx to be folded to a constant when VF is not \" \"scalable\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2424, __extension__
__PRETTY_FUNCTION__))
2423 "Expected StartIdx to be folded to a constant when VF is not "(static_cast <bool> ((State.VF.isScalable() || isa<Constant
>(StartIdx)) && "Expected StartIdx to be folded to a constant when VF is not "
"scalable") ? void (0) : __assert_fail ("(State.VF.isScalable() || isa<Constant>(StartIdx)) && \"Expected StartIdx to be folded to a constant when VF is not \" \"scalable\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2424, __extension__
__PRETTY_FUNCTION__))
2424 "scalable")(static_cast <bool> ((State.VF.isScalable() || isa<Constant
>(StartIdx)) && "Expected StartIdx to be folded to a constant when VF is not "
"scalable") ? void (0) : __assert_fail ("(State.VF.isScalable() || isa<Constant>(StartIdx)) && \"Expected StartIdx to be folded to a constant when VF is not \" \"scalable\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2424, __extension__
__PRETTY_FUNCTION__))
;
2425 auto *Mul = Builder.CreateBinOp(MulOp, StartIdx, Step);
2426 auto *Add = Builder.CreateBinOp(AddOp, ScalarIV, Mul);
2427 State.set(Def, Add, VPIteration(Part, Lane));
2428 }
2429 }
2430}
2431
2432// Generate code for the induction step. Note that induction steps are
2433// required to be loop-invariant
2434static Value *CreateStepValue(const SCEV *Step, ScalarEvolution &SE,
2435 Instruction *InsertBefore,
2436 Loop *OrigLoop = nullptr) {
2437 const DataLayout &DL = SE.getDataLayout();
2438 assert((!OrigLoop || SE.isLoopInvariant(Step, OrigLoop)) &&(static_cast <bool> ((!OrigLoop || SE.isLoopInvariant(Step
, OrigLoop)) && "Induction step should be loop invariant"
) ? void (0) : __assert_fail ("(!OrigLoop || SE.isLoopInvariant(Step, OrigLoop)) && \"Induction step should be loop invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2439, __extension__
__PRETTY_FUNCTION__))
2439 "Induction step should be loop invariant")(static_cast <bool> ((!OrigLoop || SE.isLoopInvariant(Step
, OrigLoop)) && "Induction step should be loop invariant"
) ? void (0) : __assert_fail ("(!OrigLoop || SE.isLoopInvariant(Step, OrigLoop)) && \"Induction step should be loop invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2439, __extension__
__PRETTY_FUNCTION__))
;
2440 if (auto *E = dyn_cast<SCEVUnknown>(Step))
2441 return E->getValue();
2442
2443 SCEVExpander Exp(SE, DL, "induction");
2444 return Exp.expandCodeFor(Step, Step->getType(), InsertBefore);
2445}
2446
2447/// Compute the transformed value of Index at offset StartValue using step
2448/// StepValue.
2449/// For integer induction, returns StartValue + Index * StepValue.
2450/// For pointer induction, returns StartValue[Index * StepValue].
2451/// FIXME: The newly created binary instructions should contain nsw/nuw
2452/// flags, which can be found from the original scalar operations.
2453static Value *emitTransformedIndex(IRBuilderBase &B, Value *Index,
2454 Value *StartValue, Value *Step,
2455 const InductionDescriptor &ID) {
2456 assert(Index->getType()->getScalarType() == Step->getType() &&(static_cast <bool> (Index->getType()->getScalarType
() == Step->getType() && "Index scalar type does not match StepValue type"
) ? void (0) : __assert_fail ("Index->getType()->getScalarType() == Step->getType() && \"Index scalar type does not match StepValue type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2457, __extension__
__PRETTY_FUNCTION__))
2457 "Index scalar type does not match StepValue type")(static_cast <bool> (Index->getType()->getScalarType
() == Step->getType() && "Index scalar type does not match StepValue type"
) ? void (0) : __assert_fail ("Index->getType()->getScalarType() == Step->getType() && \"Index scalar type does not match StepValue type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2457, __extension__
__PRETTY_FUNCTION__))
;
2458
2459 // Note: the IR at this point is broken. We cannot use SE to create any new
2460 // SCEV and then expand it, hoping that SCEV's simplification will give us
2461 // a more optimal code. Unfortunately, attempt of doing so on invalid IR may
2462 // lead to various SCEV crashes. So all we can do is to use builder and rely
2463 // on InstCombine for future simplifications. Here we handle some trivial
2464 // cases only.
2465 auto CreateAdd = [&B](Value *X, Value *Y) {
2466 assert(X->getType() == Y->getType() && "Types don't match!")(static_cast <bool> (X->getType() == Y->getType()
&& "Types don't match!") ? void (0) : __assert_fail (
"X->getType() == Y->getType() && \"Types don't match!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2466, __extension__
__PRETTY_FUNCTION__))
;
2467 if (auto *CX = dyn_cast<ConstantInt>(X))
2468 if (CX->isZero())
2469 return Y;
2470 if (auto *CY = dyn_cast<ConstantInt>(Y))
2471 if (CY->isZero())
2472 return X;
2473 return B.CreateAdd(X, Y);
2474 };
2475
2476 // We allow X to be a vector type, in which case Y will potentially be
2477 // splatted into a vector with the same element count.
2478 auto CreateMul = [&B](Value *X, Value *Y) {
2479 assert(X->getType()->getScalarType() == Y->getType() &&(static_cast <bool> (X->getType()->getScalarType(
) == Y->getType() && "Types don't match!") ? void (
0) : __assert_fail ("X->getType()->getScalarType() == Y->getType() && \"Types don't match!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2480, __extension__
__PRETTY_FUNCTION__))
2480 "Types don't match!")(static_cast <bool> (X->getType()->getScalarType(
) == Y->getType() && "Types don't match!") ? void (
0) : __assert_fail ("X->getType()->getScalarType() == Y->getType() && \"Types don't match!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2480, __extension__
__PRETTY_FUNCTION__))
;
2481 if (auto *CX = dyn_cast<ConstantInt>(X))
2482 if (CX->isOne())
2483 return Y;
2484 if (auto *CY = dyn_cast<ConstantInt>(Y))
2485 if (CY->isOne())
2486 return X;
2487 VectorType *XVTy = dyn_cast<VectorType>(X->getType());
2488 if (XVTy && !isa<VectorType>(Y->getType()))
2489 Y = B.CreateVectorSplat(XVTy->getElementCount(), Y);
2490 return B.CreateMul(X, Y);
2491 };
2492
2493 switch (ID.getKind()) {
2494 case InductionDescriptor::IK_IntInduction: {
2495 assert(!isa<VectorType>(Index->getType()) &&(static_cast <bool> (!isa<VectorType>(Index->getType
()) && "Vector indices not supported for integer inductions yet"
) ? void (0) : __assert_fail ("!isa<VectorType>(Index->getType()) && \"Vector indices not supported for integer inductions yet\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2496, __extension__
__PRETTY_FUNCTION__))
2496 "Vector indices not supported for integer inductions yet")(static_cast <bool> (!isa<VectorType>(Index->getType
()) && "Vector indices not supported for integer inductions yet"
) ? void (0) : __assert_fail ("!isa<VectorType>(Index->getType()) && \"Vector indices not supported for integer inductions yet\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2496, __extension__
__PRETTY_FUNCTION__))
;
2497 assert(Index->getType() == StartValue->getType() &&(static_cast <bool> (Index->getType() == StartValue->
getType() && "Index type does not match StartValue type"
) ? void (0) : __assert_fail ("Index->getType() == StartValue->getType() && \"Index type does not match StartValue type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2498, __extension__
__PRETTY_FUNCTION__))
2498 "Index type does not match StartValue type")(static_cast <bool> (Index->getType() == StartValue->
getType() && "Index type does not match StartValue type"
) ? void (0) : __assert_fail ("Index->getType() == StartValue->getType() && \"Index type does not match StartValue type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2498, __extension__
__PRETTY_FUNCTION__))
;
2499 if (isa<ConstantInt>(Step) && cast<ConstantInt>(Step)->isMinusOne())
2500 return B.CreateSub(StartValue, Index);
2501 auto *Offset = CreateMul(Index, Step);
2502 return CreateAdd(StartValue, Offset);
2503 }
2504 case InductionDescriptor::IK_PtrInduction: {
2505 assert(isa<Constant>(Step) &&(static_cast <bool> (isa<Constant>(Step) &&
"Expected constant step for pointer induction") ? void (0) :
__assert_fail ("isa<Constant>(Step) && \"Expected constant step for pointer induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2506, __extension__
__PRETTY_FUNCTION__))
2506 "Expected constant step for pointer induction")(static_cast <bool> (isa<Constant>(Step) &&
"Expected constant step for pointer induction") ? void (0) :
__assert_fail ("isa<Constant>(Step) && \"Expected constant step for pointer induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2506, __extension__
__PRETTY_FUNCTION__))
;
2507 return B.CreateGEP(ID.getElementType(), StartValue, CreateMul(Index, Step));
2508 }
2509 case InductionDescriptor::IK_FpInduction: {
2510 assert(!isa<VectorType>(Index->getType()) &&(static_cast <bool> (!isa<VectorType>(Index->getType
()) && "Vector indices not supported for FP inductions yet"
) ? void (0) : __assert_fail ("!isa<VectorType>(Index->getType()) && \"Vector indices not supported for FP inductions yet\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2511, __extension__
__PRETTY_FUNCTION__))
2511 "Vector indices not supported for FP inductions yet")(static_cast <bool> (!isa<VectorType>(Index->getType
()) && "Vector indices not supported for FP inductions yet"
) ? void (0) : __assert_fail ("!isa<VectorType>(Index->getType()) && \"Vector indices not supported for FP inductions yet\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2511, __extension__
__PRETTY_FUNCTION__))
;
2512 assert(Step->getType()->isFloatingPointTy() && "Expected FP Step value")(static_cast <bool> (Step->getType()->isFloatingPointTy
() && "Expected FP Step value") ? void (0) : __assert_fail
("Step->getType()->isFloatingPointTy() && \"Expected FP Step value\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2512, __extension__
__PRETTY_FUNCTION__))
;
2513 auto InductionBinOp = ID.getInductionBinOp();
2514 assert(InductionBinOp &&(static_cast <bool> (InductionBinOp && (InductionBinOp
->getOpcode() == Instruction::FAdd || InductionBinOp->getOpcode
() == Instruction::FSub) && "Original bin op should be defined for FP induction"
) ? void (0) : __assert_fail ("InductionBinOp && (InductionBinOp->getOpcode() == Instruction::FAdd || InductionBinOp->getOpcode() == Instruction::FSub) && \"Original bin op should be defined for FP induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2517, __extension__
__PRETTY_FUNCTION__))
2515 (InductionBinOp->getOpcode() == Instruction::FAdd ||(static_cast <bool> (InductionBinOp && (InductionBinOp
->getOpcode() == Instruction::FAdd || InductionBinOp->getOpcode
() == Instruction::FSub) && "Original bin op should be defined for FP induction"
) ? void (0) : __assert_fail ("InductionBinOp && (InductionBinOp->getOpcode() == Instruction::FAdd || InductionBinOp->getOpcode() == Instruction::FSub) && \"Original bin op should be defined for FP induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2517, __extension__
__PRETTY_FUNCTION__))
2516 InductionBinOp->getOpcode() == Instruction::FSub) &&(static_cast <bool> (InductionBinOp && (InductionBinOp
->getOpcode() == Instruction::FAdd || InductionBinOp->getOpcode
() == Instruction::FSub) && "Original bin op should be defined for FP induction"
) ? void (0) : __assert_fail ("InductionBinOp && (InductionBinOp->getOpcode() == Instruction::FAdd || InductionBinOp->getOpcode() == Instruction::FSub) && \"Original bin op should be defined for FP induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2517, __extension__
__PRETTY_FUNCTION__))
2517 "Original bin op should be defined for FP induction")(static_cast <bool> (InductionBinOp && (InductionBinOp
->getOpcode() == Instruction::FAdd || InductionBinOp->getOpcode
() == Instruction::FSub) && "Original bin op should be defined for FP induction"
) ? void (0) : __assert_fail ("InductionBinOp && (InductionBinOp->getOpcode() == Instruction::FAdd || InductionBinOp->getOpcode() == Instruction::FSub) && \"Original bin op should be defined for FP induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2517, __extension__
__PRETTY_FUNCTION__))
;
2518
2519 Value *MulExp = B.CreateFMul(Step, Index);
2520 return B.CreateBinOp(InductionBinOp->getOpcode(), StartValue, MulExp,
2521 "induction");
2522 }
2523 case InductionDescriptor::IK_NoInduction:
2524 return nullptr;
2525 }
2526 llvm_unreachable("invalid enum")::llvm::llvm_unreachable_internal("invalid enum", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 2526)
;
2527}
2528
2529void InnerLoopVectorizer::packScalarIntoVectorValue(VPValue *Def,
2530 const VPIteration &Instance,
2531 VPTransformState &State) {
2532 Value *ScalarInst = State.get(Def, Instance);
2533 Value *VectorValue = State.get(Def, Instance.Part);
2534 VectorValue = Builder.CreateInsertElement(
2535 VectorValue, ScalarInst,
2536 Instance.Lane.getAsRuntimeExpr(State.Builder, VF));
2537 State.set(Def, VectorValue, Instance.Part);
2538}
2539
2540// Return whether we allow using masked interleave-groups (for dealing with
2541// strided loads/stores that reside in predicated blocks, or for dealing
2542// with gaps).
2543static bool useMaskedInterleavedAccesses(const TargetTransformInfo &TTI) {
2544 // If an override option has been passed in for interleaved accesses, use it.
2545 if (EnableMaskedInterleavedMemAccesses.getNumOccurrences() > 0)
2546 return EnableMaskedInterleavedMemAccesses;
2547
2548 return TTI.enableMaskedInterleavedAccessVectorization();
2549}
2550
2551// Try to vectorize the interleave group that \p Instr belongs to.
2552//
2553// E.g. Translate following interleaved load group (factor = 3):
2554// for (i = 0; i < N; i+=3) {
2555// R = Pic[i]; // Member of index 0
2556// G = Pic[i+1]; // Member of index 1
2557// B = Pic[i+2]; // Member of index 2
2558// ... // do something to R, G, B
2559// }
2560// To:
2561// %wide.vec = load <12 x i32> ; Read 4 tuples of R,G,B
2562// %R.vec = shuffle %wide.vec, poison, <0, 3, 6, 9> ; R elements
2563// %G.vec = shuffle %wide.vec, poison, <1, 4, 7, 10> ; G elements
2564// %B.vec = shuffle %wide.vec, poison, <2, 5, 8, 11> ; B elements
2565//
2566// Or translate following interleaved store group (factor = 3):
2567// for (i = 0; i < N; i+=3) {
2568// ... do something to R, G, B
2569// Pic[i] = R; // Member of index 0
2570// Pic[i+1] = G; // Member of index 1
2571// Pic[i+2] = B; // Member of index 2
2572// }
2573// To:
2574// %R_G.vec = shuffle %R.vec, %G.vec, <0, 1, 2, ..., 7>
2575// %B_U.vec = shuffle %B.vec, poison, <0, 1, 2, 3, u, u, u, u>
2576// %interleaved.vec = shuffle %R_G.vec, %B_U.vec,
2577// <0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11> ; Interleave R,G,B elements
2578// store <12 x i32> %interleaved.vec ; Write 4 tuples of R,G,B
2579void InnerLoopVectorizer::vectorizeInterleaveGroup(
2580 const InterleaveGroup<Instruction> *Group, ArrayRef<VPValue *> VPDefs,
2581 VPTransformState &State, VPValue *Addr, ArrayRef<VPValue *> StoredValues,
2582 VPValue *BlockInMask) {
2583 Instruction *Instr = Group->getInsertPos();
2584 const DataLayout &DL = Instr->getModule()->getDataLayout();
2585
2586 // Prepare for the vector type of the interleaved load/store.
2587 Type *ScalarTy = getLoadStoreType(Instr);
2588 unsigned InterleaveFactor = Group->getFactor();
2589 assert(!VF.isScalable() && "scalable vectors not yet supported.")(static_cast <bool> (!VF.isScalable() && "scalable vectors not yet supported."
) ? void (0) : __assert_fail ("!VF.isScalable() && \"scalable vectors not yet supported.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2589, __extension__
__PRETTY_FUNCTION__))
;
2590 auto *VecTy = VectorType::get(ScalarTy, VF * InterleaveFactor);
2591
2592 // Prepare for the new pointers.
2593 SmallVector<Value *, 2> AddrParts;
2594 unsigned Index = Group->getIndex(Instr);
2595
2596 // TODO: extend the masked interleaved-group support to reversed access.
2597 assert((!BlockInMask || !Group->isReverse()) &&(static_cast <bool> ((!BlockInMask || !Group->isReverse
()) && "Reversed masked interleave-group not supported."
) ? void (0) : __assert_fail ("(!BlockInMask || !Group->isReverse()) && \"Reversed masked interleave-group not supported.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2598, __extension__
__PRETTY_FUNCTION__))
2598 "Reversed masked interleave-group not supported.")(static_cast <bool> ((!BlockInMask || !Group->isReverse
()) && "Reversed masked interleave-group not supported."
) ? void (0) : __assert_fail ("(!BlockInMask || !Group->isReverse()) && \"Reversed masked interleave-group not supported.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2598, __extension__
__PRETTY_FUNCTION__))
;
2599
2600 // If the group is reverse, adjust the index to refer to the last vector lane
2601 // instead of the first. We adjust the index from the first vector lane,
2602 // rather than directly getting the pointer for lane VF - 1, because the
2603 // pointer operand of the interleaved access is supposed to be uniform. For
2604 // uniform instructions, we're only required to generate a value for the
2605 // first vector lane in each unroll iteration.
2606 if (Group->isReverse())
2607 Index += (VF.getKnownMinValue() - 1) * Group->getFactor();
2608
2609 for (unsigned Part = 0; Part < UF; Part++) {
2610 Value *AddrPart = State.get(Addr, VPIteration(Part, 0));
2611 setDebugLocFromInst(AddrPart);
2612
2613 // Notice current instruction could be any index. Need to adjust the address
2614 // to the member of index 0.
2615 //
2616 // E.g. a = A[i+1]; // Member of index 1 (Current instruction)
2617 // b = A[i]; // Member of index 0
2618 // Current pointer is pointed to A[i+1], adjust it to A[i].
2619 //
2620 // E.g. A[i+1] = a; // Member of index 1
2621 // A[i] = b; // Member of index 0
2622 // A[i+2] = c; // Member of index 2 (Current instruction)
2623 // Current pointer is pointed to A[i+2], adjust it to A[i].
2624
2625 bool InBounds = false;
2626 if (auto *gep = dyn_cast<GetElementPtrInst>(AddrPart->stripPointerCasts()))
2627 InBounds = gep->isInBounds();
2628 AddrPart = Builder.CreateGEP(ScalarTy, AddrPart, Builder.getInt32(-Index));
2629 cast<GetElementPtrInst>(AddrPart)->setIsInBounds(InBounds);
2630
2631 // Cast to the vector pointer type.
2632 unsigned AddressSpace = AddrPart->getType()->getPointerAddressSpace();
2633 Type *PtrTy = VecTy->getPointerTo(AddressSpace);
2634 AddrParts.push_back(Builder.CreateBitCast(AddrPart, PtrTy));
2635 }
2636
2637 setDebugLocFromInst(Instr);
2638 Value *PoisonVec = PoisonValue::get(VecTy);
2639
2640 Value *MaskForGaps = nullptr;
2641 if (Group->requiresScalarEpilogue() && !Cost->isScalarEpilogueAllowed()) {
2642 MaskForGaps = createBitMaskForGaps(Builder, VF.getKnownMinValue(), *Group);
2643 assert(MaskForGaps && "Mask for Gaps is required but it is null")(static_cast <bool> (MaskForGaps && "Mask for Gaps is required but it is null"
) ? void (0) : __assert_fail ("MaskForGaps && \"Mask for Gaps is required but it is null\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2643, __extension__
__PRETTY_FUNCTION__))
;
2644 }
2645
2646 // Vectorize the interleaved load group.
2647 if (isa<LoadInst>(Instr)) {
2648 // For each unroll part, create a wide load for the group.
2649 SmallVector<Value *, 2> NewLoads;
2650 for (unsigned Part = 0; Part < UF; Part++) {
2651 Instruction *NewLoad;
2652 if (BlockInMask || MaskForGaps) {
2653 assert(useMaskedInterleavedAccesses(*TTI) &&(static_cast <bool> (useMaskedInterleavedAccesses(*TTI)
&& "masked interleaved groups are not allowed.") ? void
(0) : __assert_fail ("useMaskedInterleavedAccesses(*TTI) && \"masked interleaved groups are not allowed.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2654, __extension__
__PRETTY_FUNCTION__))
2654 "masked interleaved groups are not allowed.")(static_cast <bool> (useMaskedInterleavedAccesses(*TTI)
&& "masked interleaved groups are not allowed.") ? void
(0) : __assert_fail ("useMaskedInterleavedAccesses(*TTI) && \"masked interleaved groups are not allowed.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2654, __extension__
__PRETTY_FUNCTION__))
;
2655 Value *GroupMask = MaskForGaps;
2656 if (BlockInMask) {
2657 Value *BlockInMaskPart = State.get(BlockInMask, Part);
2658 Value *ShuffledMask = Builder.CreateShuffleVector(
2659 BlockInMaskPart,
2660 createReplicatedMask(InterleaveFactor, VF.getKnownMinValue()),
2661 "interleaved.mask");
2662 GroupMask = MaskForGaps
2663 ? Builder.CreateBinOp(Instruction::And, ShuffledMask,
2664 MaskForGaps)
2665 : ShuffledMask;
2666 }
2667 NewLoad =
2668 Builder.CreateMaskedLoad(VecTy, AddrParts[Part], Group->getAlign(),
2669 GroupMask, PoisonVec, "wide.masked.vec");
2670 }
2671 else
2672 NewLoad = Builder.CreateAlignedLoad(VecTy, AddrParts[Part],
2673 Group->getAlign(), "wide.vec");
2674 Group->addMetadata(NewLoad);
2675 NewLoads.push_back(NewLoad);
2676 }
2677
2678 // For each member in the group, shuffle out the appropriate data from the
2679 // wide loads.
2680 unsigned J = 0;
2681 for (unsigned I = 0; I < InterleaveFactor; ++I) {
2682 Instruction *Member = Group->getMember(I);
2683
2684 // Skip the gaps in the group.
2685 if (!Member)
2686 continue;
2687
2688 auto StrideMask =
2689 createStrideMask(I, InterleaveFactor, VF.getKnownMinValue());
2690 for (unsigned Part = 0; Part < UF; Part++) {
2691 Value *StridedVec = Builder.CreateShuffleVector(
2692 NewLoads[Part], StrideMask, "strided.vec");
2693
2694 // If this member has different type, cast the result type.
2695 if (Member->getType() != ScalarTy) {
2696 assert(!VF.isScalable() && "VF is assumed to be non scalable.")(static_cast <bool> (!VF.isScalable() && "VF is assumed to be non scalable."
) ? void (0) : __assert_fail ("!VF.isScalable() && \"VF is assumed to be non scalable.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2696, __extension__
__PRETTY_FUNCTION__))
;
2697 VectorType *OtherVTy = VectorType::get(Member->getType(), VF);
2698 StridedVec = createBitOrPointerCast(StridedVec, OtherVTy, DL);
2699 }
2700
2701 if (Group->isReverse())
2702 StridedVec = Builder.CreateVectorReverse(StridedVec, "reverse");
2703
2704 State.set(VPDefs[J], StridedVec, Part);
2705 }
2706 ++J;
2707 }
2708 return;
2709 }
2710
2711 // The sub vector type for current instruction.
2712 auto *SubVT = VectorType::get(ScalarTy, VF);
2713
2714 // Vectorize the interleaved store group.
2715 MaskForGaps = createBitMaskForGaps(Builder, VF.getKnownMinValue(), *Group);
2716 assert((!MaskForGaps || useMaskedInterleavedAccesses(*TTI)) &&(static_cast <bool> ((!MaskForGaps || useMaskedInterleavedAccesses
(*TTI)) && "masked interleaved groups are not allowed."
) ? void (0) : __assert_fail ("(!MaskForGaps || useMaskedInterleavedAccesses(*TTI)) && \"masked interleaved groups are not allowed.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2717, __extension__
__PRETTY_FUNCTION__))
2717 "masked interleaved groups are not allowed.")(static_cast <bool> ((!MaskForGaps || useMaskedInterleavedAccesses
(*TTI)) && "masked interleaved groups are not allowed."
) ? void (0) : __assert_fail ("(!MaskForGaps || useMaskedInterleavedAccesses(*TTI)) && \"masked interleaved groups are not allowed.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2717, __extension__
__PRETTY_FUNCTION__))
;
2718 assert((!MaskForGaps || !VF.isScalable()) &&(static_cast <bool> ((!MaskForGaps || !VF.isScalable())
&& "masking gaps for scalable vectors is not yet supported."
) ? void (0) : __assert_fail ("(!MaskForGaps || !VF.isScalable()) && \"masking gaps for scalable vectors is not yet supported.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2719, __extension__
__PRETTY_FUNCTION__))
2719 "masking gaps for scalable vectors is not yet supported.")(static_cast <bool> ((!MaskForGaps || !VF.isScalable())
&& "masking gaps for scalable vectors is not yet supported."
) ? void (0) : __assert_fail ("(!MaskForGaps || !VF.isScalable()) && \"masking gaps for scalable vectors is not yet supported.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2719, __extension__
__PRETTY_FUNCTION__))
;
2720 for (unsigned Part = 0; Part < UF; Part++) {
2721 // Collect the stored vector from each member.
2722 SmallVector<Value *, 4> StoredVecs;
2723 for (unsigned i = 0; i < InterleaveFactor; i++) {
2724 assert((Group->getMember(i) || MaskForGaps) &&(static_cast <bool> ((Group->getMember(i) || MaskForGaps
) && "Fail to get a member from an interleaved store group"
) ? void (0) : __assert_fail ("(Group->getMember(i) || MaskForGaps) && \"Fail to get a member from an interleaved store group\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2725, __extension__
__PRETTY_FUNCTION__))
2725 "Fail to get a member from an interleaved store group")(static_cast <bool> ((Group->getMember(i) || MaskForGaps
) && "Fail to get a member from an interleaved store group"
) ? void (0) : __assert_fail ("(Group->getMember(i) || MaskForGaps) && \"Fail to get a member from an interleaved store group\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2725, __extension__
__PRETTY_FUNCTION__))
;
2726 Instruction *Member = Group->getMember(i);
2727
2728 // Skip the gaps in the group.
2729 if (!Member) {
2730 Value *Undef = PoisonValue::get(SubVT);
2731 StoredVecs.push_back(Undef);
2732 continue;
2733 }
2734
2735 Value *StoredVec = State.get(StoredValues[i], Part);
2736
2737 if (Group->isReverse())
2738 StoredVec = Builder.CreateVectorReverse(StoredVec, "reverse");
2739
2740 // If this member has different type, cast it to a unified type.
2741
2742 if (StoredVec->getType() != SubVT)
2743 StoredVec = createBitOrPointerCast(StoredVec, SubVT, DL);
2744
2745 StoredVecs.push_back(StoredVec);
2746 }
2747
2748 // Concatenate all vectors into a wide vector.
2749 Value *WideVec = concatenateVectors(Builder, StoredVecs);
2750
2751 // Interleave the elements in the wide vector.
2752 Value *IVec = Builder.CreateShuffleVector(
2753 WideVec, createInterleaveMask(VF.getKnownMinValue(), InterleaveFactor),
2754 "interleaved.vec");
2755
2756 Instruction *NewStoreInstr;
2757 if (BlockInMask || MaskForGaps) {
2758 Value *GroupMask = MaskForGaps;
2759 if (BlockInMask) {
2760 Value *BlockInMaskPart = State.get(BlockInMask, Part);
2761 Value *ShuffledMask = Builder.CreateShuffleVector(
2762 BlockInMaskPart,
2763 createReplicatedMask(InterleaveFactor, VF.getKnownMinValue()),
2764 "interleaved.mask");
2765 GroupMask = MaskForGaps ? Builder.CreateBinOp(Instruction::And,
2766 ShuffledMask, MaskForGaps)
2767 : ShuffledMask;
2768 }
2769 NewStoreInstr = Builder.CreateMaskedStore(IVec, AddrParts[Part],
2770 Group->getAlign(), GroupMask);
2771 } else
2772 NewStoreInstr =
2773 Builder.CreateAlignedStore(IVec, AddrParts[Part], Group->getAlign());
2774
2775 Group->addMetadata(NewStoreInstr);
2776 }
2777}
2778
2779void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr,
2780 VPReplicateRecipe *RepRecipe,
2781 const VPIteration &Instance,
2782 bool IfPredicateInstr,
2783 VPTransformState &State) {
2784 assert(!Instr->getType()->isAggregateType() && "Can't handle vectors")(static_cast <bool> (!Instr->getType()->isAggregateType
() && "Can't handle vectors") ? void (0) : __assert_fail
("!Instr->getType()->isAggregateType() && \"Can't handle vectors\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2784, __extension__
__PRETTY_FUNCTION__))
;
2785
2786 // llvm.experimental.noalias.scope.decl intrinsics must only be duplicated for
2787 // the first lane and part.
2788 if (isa<NoAliasScopeDeclInst>(Instr))
2789 if (!Instance.isFirstIteration())
2790 return;
2791
2792 setDebugLocFromInst(Instr);
2793
2794 // Does this instruction return a value ?
2795 bool IsVoidRetTy = Instr->getType()->isVoidTy();
2796
2797 Instruction *Cloned = Instr->clone();
2798 if (!IsVoidRetTy)
2799 Cloned->setName(Instr->getName() + ".cloned");
2800
2801 // If the scalarized instruction contributes to the address computation of a
2802 // widen masked load/store which was in a basic block that needed predication
2803 // and is not predicated after vectorization, we can't propagate
2804 // poison-generating flags (nuw/nsw, exact, inbounds, etc.). The scalarized
2805 // instruction could feed a poison value to the base address of the widen
2806 // load/store.
2807 if (State.MayGeneratePoisonRecipes.contains(RepRecipe))
2808 Cloned->dropPoisonGeneratingFlags();
2809
2810 State.Builder.SetInsertPoint(Builder.GetInsertBlock(),
2811 Builder.GetInsertPoint());
2812 // Replace the operands of the cloned instructions with their scalar
2813 // equivalents in the new loop.
2814 for (auto &I : enumerate(RepRecipe->operands())) {
2815 auto InputInstance = Instance;
2816 VPValue *Operand = I.value();
2817 VPReplicateRecipe *OperandR = dyn_cast<VPReplicateRecipe>(Operand);
2818 if (OperandR && OperandR->isUniform())
2819 InputInstance.Lane = VPLane::getFirstLane();
2820 Cloned->setOperand(I.index(), State.get(Operand, InputInstance));
2821 }
2822 addNewMetadata(Cloned, Instr);
2823
2824 // Place the cloned scalar in the new loop.
2825 Builder.Insert(Cloned);
2826
2827 State.set(RepRecipe, Cloned, Instance);
2828
2829 // If we just cloned a new assumption, add it the assumption cache.
2830 if (auto *II = dyn_cast<AssumeInst>(Cloned))
2831 AC->registerAssumption(II);
2832
2833 // End if-block.
2834 if (IfPredicateInstr)
2835 PredicatedInstructions.push_back(Cloned);
2836}
2837
2838void InnerLoopVectorizer::createHeaderBranch(Loop *L) {
2839 BasicBlock *Header = L->getHeader();
2840 assert(!L->getLoopLatch() && "loop should not have a latch at this point")(static_cast <bool> (!L->getLoopLatch() && "loop should not have a latch at this point"
) ? void (0) : __assert_fail ("!L->getLoopLatch() && \"loop should not have a latch at this point\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2840, __extension__
__PRETTY_FUNCTION__))
;
2841
2842 IRBuilder<> B(Header->getTerminator());
2843 Instruction *OldInst =
2844 getDebugLocFromInstOrOperands(Legal->getPrimaryInduction());
2845 setDebugLocFromInst(OldInst, &B);
2846
2847 // Connect the header to the exit and header blocks and replace the old
2848 // terminator.
2849 B.CreateCondBr(B.getTrue(), L->getUniqueExitBlock(), Header);
2850
2851 // Now we have two terminators. Remove the old one from the block.
2852 Header->getTerminator()->eraseFromParent();
2853}
2854
2855Value *InnerLoopVectorizer::getOrCreateTripCount(Loop *L) {
2856 if (TripCount)
2857 return TripCount;
2858
2859 assert(L && "Create Trip Count for null loop.")(static_cast <bool> (L && "Create Trip Count for null loop."
) ? void (0) : __assert_fail ("L && \"Create Trip Count for null loop.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2859, __extension__
__PRETTY_FUNCTION__))
;
2860 IRBuilder<> Builder(L->getLoopPreheader()->getTerminator());
2861 // Find the loop boundaries.
2862 ScalarEvolution *SE = PSE.getSE();
2863 const SCEV *BackedgeTakenCount = PSE.getBackedgeTakenCount();
2864 assert(!isa<SCEVCouldNotCompute>(BackedgeTakenCount) &&(static_cast <bool> (!isa<SCEVCouldNotCompute>(BackedgeTakenCount
) && "Invalid loop count") ? void (0) : __assert_fail
("!isa<SCEVCouldNotCompute>(BackedgeTakenCount) && \"Invalid loop count\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2865, __extension__
__PRETTY_FUNCTION__))
2865 "Invalid loop count")(static_cast <bool> (!isa<SCEVCouldNotCompute>(BackedgeTakenCount
) && "Invalid loop count") ? void (0) : __assert_fail
("!isa<SCEVCouldNotCompute>(BackedgeTakenCount) && \"Invalid loop count\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2865, __extension__
__PRETTY_FUNCTION__))
;
2866
2867 Type *IdxTy = Legal->getWidestInductionType();
2868 assert(IdxTy && "No type for induction")(static_cast <bool> (IdxTy && "No type for induction"
) ? void (0) : __assert_fail ("IdxTy && \"No type for induction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2868, __extension__
__PRETTY_FUNCTION__))
;
2869
2870 // The exit count might have the type of i64 while the phi is i32. This can
2871 // happen if we have an induction variable that is sign extended before the
2872 // compare. The only way that we get a backedge taken count is that the
2873 // induction variable was signed and as such will not overflow. In such a case
2874 // truncation is legal.
2875 if (SE->getTypeSizeInBits(BackedgeTakenCount->getType()) >
2876 IdxTy->getPrimitiveSizeInBits())
2877 BackedgeTakenCount = SE->getTruncateOrNoop(BackedgeTakenCount, IdxTy);
2878 BackedgeTakenCount = SE->getNoopOrZeroExtend(BackedgeTakenCount, IdxTy);
2879
2880 // Get the total trip count from the count by adding 1.
2881 const SCEV *ExitCount = SE->getAddExpr(
2882 BackedgeTakenCount, SE->getOne(BackedgeTakenCount->getType()));
2883
2884 const DataLayout &DL = L->getHeader()->getModule()->getDataLayout();
2885
2886 // Expand the trip count and place the new instructions in the preheader.
2887 // Notice that the pre-header does not change, only the loop body.
2888 SCEVExpander Exp(*SE, DL, "induction");
2889
2890 // Count holds the overall loop count (N).
2891 TripCount = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
2892 L->getLoopPreheader()->getTerminator());
2893
2894 if (TripCount->getType()->isPointerTy())
2895 TripCount =
2896 CastInst::CreatePointerCast(TripCount, IdxTy, "exitcount.ptrcnt.to.int",
2897 L->getLoopPreheader()->getTerminator());
2898
2899 return TripCount;
2900}
2901
2902Value *InnerLoopVectorizer::getOrCreateVectorTripCount(Loop *L) {
2903 if (VectorTripCount)
5
Assuming field 'VectorTripCount' is null
6
Taking false branch
2904 return VectorTripCount;
2905
2906 Value *TC = getOrCreateTripCount(L);
2907 IRBuilder<> Builder(L->getLoopPreheader()->getTerminator());
7
Called C++ object pointer is null
2908
2909 Type *Ty = TC->getType();
2910 // This is where we can make the step a runtime constant.
2911 Value *Step = createStepForVF(Builder, Ty, VF, UF);
2912
2913 // If the tail is to be folded by masking, round the number of iterations N
2914 // up to a multiple of Step instead of rounding down. This is done by first
2915 // adding Step-1 and then rounding down. Note that it's ok if this addition
2916 // overflows: the vector induction variable will eventually wrap to zero given
2917 // that it starts at zero and its Step is a power of two; the loop will then
2918 // exit, with the last early-exit vector comparison also producing all-true.
2919 if (Cost->foldTailByMasking()) {
2920 assert(isPowerOf2_32(VF.getKnownMinValue() * UF) &&(static_cast <bool> (isPowerOf2_32(VF.getKnownMinValue(
) * UF) && "VF*UF must be a power of 2 when folding tail by masking"
) ? void (0) : __assert_fail ("isPowerOf2_32(VF.getKnownMinValue() * UF) && \"VF*UF must be a power of 2 when folding tail by masking\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2921, __extension__
__PRETTY_FUNCTION__))
2921 "VF*UF must be a power of 2 when folding tail by masking")(static_cast <bool> (isPowerOf2_32(VF.getKnownMinValue(
) * UF) && "VF*UF must be a power of 2 when folding tail by masking"
) ? void (0) : __assert_fail ("isPowerOf2_32(VF.getKnownMinValue() * UF) && \"VF*UF must be a power of 2 when folding tail by masking\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2921, __extension__
__PRETTY_FUNCTION__))
;
2922 Value *NumLanes = getRuntimeVF(Builder, Ty, VF * UF);
2923 TC = Builder.CreateAdd(
2924 TC, Builder.CreateSub(NumLanes, ConstantInt::get(Ty, 1)), "n.rnd.up");
2925 }
2926
2927 // Now we need to generate the expression for the part of the loop that the
2928 // vectorized body will execute. This is equal to N - (N % Step) if scalar
2929 // iterations are not required for correctness, or N - Step, otherwise. Step
2930 // is equal to the vectorization factor (number of SIMD elements) times the
2931 // unroll factor (number of SIMD instructions).
2932 Value *R = Builder.CreateURem(TC, Step, "n.mod.vf");
2933
2934 // There are cases where we *must* run at least one iteration in the remainder
2935 // loop. See the cost model for when this can happen. If the step evenly
2936 // divides the trip count, we set the remainder to be equal to the step. If
2937 // the step does not evenly divide the trip count, no adjustment is necessary
2938 // since there will already be scalar iterations. Note that the minimum
2939 // iterations check ensures that N >= Step.
2940 if (Cost->requiresScalarEpilogue(VF)) {
2941 auto *IsZero = Builder.CreateICmpEQ(R, ConstantInt::get(R->getType(), 0));
2942 R = Builder.CreateSelect(IsZero, Step, R);
2943 }
2944
2945 VectorTripCount = Builder.CreateSub(TC, R, "n.vec");
2946
2947 return VectorTripCount;
2948}
2949
2950Value *InnerLoopVectorizer::createBitOrPointerCast(Value *V, VectorType *DstVTy,
2951 const DataLayout &DL) {
2952 // Verify that V is a vector type with same number of elements as DstVTy.
2953 auto *DstFVTy = cast<FixedVectorType>(DstVTy);
2954 unsigned VF = DstFVTy->getNumElements();
2955 auto *SrcVecTy = cast<FixedVectorType>(V->getType());
2956 assert((VF == SrcVecTy->getNumElements()) && "Vector dimensions do not match")(static_cast <bool> ((VF == SrcVecTy->getNumElements
()) && "Vector dimensions do not match") ? void (0) :
__assert_fail ("(VF == SrcVecTy->getNumElements()) && \"Vector dimensions do not match\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2956, __extension__
__PRETTY_FUNCTION__))
;
2957 Type *SrcElemTy = SrcVecTy->getElementType();
2958 Type *DstElemTy = DstFVTy->getElementType();
2959 assert((DL.getTypeSizeInBits(SrcElemTy) == DL.getTypeSizeInBits(DstElemTy)) &&(static_cast <bool> ((DL.getTypeSizeInBits(SrcElemTy) ==
DL.getTypeSizeInBits(DstElemTy)) && "Vector elements must have same size"
) ? void (0) : __assert_fail ("(DL.getTypeSizeInBits(SrcElemTy) == DL.getTypeSizeInBits(DstElemTy)) && \"Vector elements must have same size\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2960, __extension__
__PRETTY_FUNCTION__))
2960 "Vector elements must have same size")(static_cast <bool> ((DL.getTypeSizeInBits(SrcElemTy) ==
DL.getTypeSizeInBits(DstElemTy)) && "Vector elements must have same size"
) ? void (0) : __assert_fail ("(DL.getTypeSizeInBits(SrcElemTy) == DL.getTypeSizeInBits(DstElemTy)) && \"Vector elements must have same size\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2960, __extension__
__PRETTY_FUNCTION__))
;
2961
2962 // Do a direct cast if element types are castable.
2963 if (CastInst::isBitOrNoopPointerCastable(SrcElemTy, DstElemTy, DL)) {
2964 return Builder.CreateBitOrPointerCast(V, DstFVTy);
2965 }
2966 // V cannot be directly casted to desired vector type.
2967 // May happen when V is a floating point vector but DstVTy is a vector of
2968 // pointers or vice-versa. Handle this using a two-step bitcast using an
2969 // intermediate Integer type for the bitcast i.e. Ptr <-> Int <-> Float.
2970 assert((DstElemTy->isPointerTy() != SrcElemTy->isPointerTy()) &&(static_cast <bool> ((DstElemTy->isPointerTy() != SrcElemTy
->isPointerTy()) && "Only one type should be a pointer type"
) ? void (0) : __assert_fail ("(DstElemTy->isPointerTy() != SrcElemTy->isPointerTy()) && \"Only one type should be a pointer type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2971, __extension__
__PRETTY_FUNCTION__))
2971 "Only one type should be a pointer type")(static_cast <bool> ((DstElemTy->isPointerTy() != SrcElemTy
->isPointerTy()) && "Only one type should be a pointer type"
) ? void (0) : __assert_fail ("(DstElemTy->isPointerTy() != SrcElemTy->isPointerTy()) && \"Only one type should be a pointer type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2971, __extension__
__PRETTY_FUNCTION__))
;
2972 assert((DstElemTy->isFloatingPointTy() != SrcElemTy->isFloatingPointTy()) &&(static_cast <bool> ((DstElemTy->isFloatingPointTy()
!= SrcElemTy->isFloatingPointTy()) && "Only one type should be a floating point type"
) ? void (0) : __assert_fail ("(DstElemTy->isFloatingPointTy() != SrcElemTy->isFloatingPointTy()) && \"Only one type should be a floating point type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2973, __extension__
__PRETTY_FUNCTION__))
2973 "Only one type should be a floating point type")(static_cast <bool> ((DstElemTy->isFloatingPointTy()
!= SrcElemTy->isFloatingPointTy()) && "Only one type should be a floating point type"
) ? void (0) : __assert_fail ("(DstElemTy->isFloatingPointTy() != SrcElemTy->isFloatingPointTy()) && \"Only one type should be a floating point type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 2973, __extension__
__PRETTY_FUNCTION__))
;
2974 Type *IntTy =
2975 IntegerType::getIntNTy(V->getContext(), DL.getTypeSizeInBits(SrcElemTy));
2976 auto *VecIntTy = FixedVectorType::get(IntTy, VF);
2977 Value *CastVal = Builder.CreateBitOrPointerCast(V, VecIntTy);
2978 return Builder.CreateBitOrPointerCast(CastVal, DstFVTy);
2979}
2980
2981void InnerLoopVectorizer::emitMinimumIterationCountCheck(Loop *L,
2982 BasicBlock *Bypass) {
2983 Value *Count = getOrCreateTripCount(L);
2984 // Reuse existing vector loop preheader for TC checks.
2985 // Note that new preheader block is generated for vector loop.
2986 BasicBlock *const TCCheckBlock = LoopVectorPreHeader;
2987 IRBuilder<> Builder(TCCheckBlock->getTerminator());
2988
2989 // Generate code to check if the loop's trip count is less than VF * UF, or
2990 // equal to it in case a scalar epilogue is required; this implies that the
2991 // vector trip count is zero. This check also covers the case where adding one
2992 // to the backedge-taken count overflowed leading to an incorrect trip count
2993 // of zero. In this case we will also jump to the scalar loop.
2994 auto P = Cost->requiresScalarEpilogue(VF) ? ICmpInst::ICMP_ULE
2995 : ICmpInst::ICMP_ULT;
2996
2997 // If tail is to be folded, vector loop takes care of all iterations.
2998 Value *CheckMinIters = Builder.getFalse();
2999 if (!Cost->foldTailByMasking()) {
3000 Value *Step = createStepForVF(Builder, Count->getType(), VF, UF);
3001 CheckMinIters = Builder.CreateICmp(P, Count, Step, "min.iters.check");
3002 }
3003 // Create new preheader for vector loop.
3004 LoopVectorPreHeader =
3005 SplitBlock(TCCheckBlock, TCCheckBlock->getTerminator(), DT, LI, nullptr,
3006 "vector.ph");
3007
3008 assert(DT->properlyDominates(DT->getNode(TCCheckBlock),(static_cast <bool> (DT->properlyDominates(DT->getNode
(TCCheckBlock), DT->getNode(Bypass)->getIDom()) &&
"TC check is expected to dominate Bypass") ? void (0) : __assert_fail
("DT->properlyDominates(DT->getNode(TCCheckBlock), DT->getNode(Bypass)->getIDom()) && \"TC check is expected to dominate Bypass\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3010, __extension__
__PRETTY_FUNCTION__))
3009 DT->getNode(Bypass)->getIDom()) &&(static_cast <bool> (DT->properlyDominates(DT->getNode
(TCCheckBlock), DT->getNode(Bypass)->getIDom()) &&
"TC check is expected to dominate Bypass") ? void (0) : __assert_fail
("DT->properlyDominates(DT->getNode(TCCheckBlock), DT->getNode(Bypass)->getIDom()) && \"TC check is expected to dominate Bypass\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3010, __extension__
__PRETTY_FUNCTION__))
3010 "TC check is expected to dominate Bypass")(static_cast <bool> (DT->properlyDominates(DT->getNode
(TCCheckBlock), DT->getNode(Bypass)->getIDom()) &&
"TC check is expected to dominate Bypass") ? void (0) : __assert_fail
("DT->properlyDominates(DT->getNode(TCCheckBlock), DT->getNode(Bypass)->getIDom()) && \"TC check is expected to dominate Bypass\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3010, __extension__
__PRETTY_FUNCTION__))
;
3011
3012 // Update dominator for Bypass & LoopExit (if needed).
3013 DT->changeImmediateDominator(Bypass, TCCheckBlock);
3014 if (!Cost->requiresScalarEpilogue(VF))
3015 // If there is an epilogue which must run, there's no edge from the
3016 // middle block to exit blocks and thus no need to update the immediate
3017 // dominator of the exit blocks.
3018 DT->changeImmediateDominator(LoopExitBlock, TCCheckBlock);
3019
3020 ReplaceInstWithInst(
3021 TCCheckBlock->getTerminator(),
3022 BranchInst::Create(Bypass, LoopVectorPreHeader, CheckMinIters));
3023 LoopBypassBlocks.push_back(TCCheckBlock);
3024}
3025
3026BasicBlock *InnerLoopVectorizer::emitSCEVChecks(BasicBlock *Bypass) {
3027
3028 BasicBlock *const SCEVCheckBlock =
3029 RTChecks.emitSCEVChecks(Bypass, LoopVectorPreHeader, LoopExitBlock);
3030 if (!SCEVCheckBlock)
3031 return nullptr;
3032
3033 assert(!(SCEVCheckBlock->getParent()->hasOptSize() ||(static_cast <bool> (!(SCEVCheckBlock->getParent()->
hasOptSize() || (OptForSizeBasedOnProfile && Cost->
Hints->getForce() != LoopVectorizeHints::FK_Enabled)) &&
"Cannot SCEV check stride or overflow when optimizing for size"
) ? void (0) : __assert_fail ("!(SCEVCheckBlock->getParent()->hasOptSize() || (OptForSizeBasedOnProfile && Cost->Hints->getForce() != LoopVectorizeHints::FK_Enabled)) && \"Cannot SCEV check stride or overflow when optimizing for size\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3036, __extension__
__PRETTY_FUNCTION__))
3034 (OptForSizeBasedOnProfile &&(static_cast <bool> (!(SCEVCheckBlock->getParent()->
hasOptSize() || (OptForSizeBasedOnProfile && Cost->
Hints->getForce() != LoopVectorizeHints::FK_Enabled)) &&
"Cannot SCEV check stride or overflow when optimizing for size"
) ? void (0) : __assert_fail ("!(SCEVCheckBlock->getParent()->hasOptSize() || (OptForSizeBasedOnProfile && Cost->Hints->getForce() != LoopVectorizeHints::FK_Enabled)) && \"Cannot SCEV check stride or overflow when optimizing for size\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3036, __extension__
__PRETTY_FUNCTION__))
3035 Cost->Hints->getForce() != LoopVectorizeHints::FK_Enabled)) &&(static_cast <bool> (!(SCEVCheckBlock->getParent()->
hasOptSize() || (OptForSizeBasedOnProfile && Cost->
Hints->getForce() != LoopVectorizeHints::FK_Enabled)) &&
"Cannot SCEV check stride or overflow when optimizing for size"
) ? void (0) : __assert_fail ("!(SCEVCheckBlock->getParent()->hasOptSize() || (OptForSizeBasedOnProfile && Cost->Hints->getForce() != LoopVectorizeHints::FK_Enabled)) && \"Cannot SCEV check stride or overflow when optimizing for size\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3036, __extension__
__PRETTY_FUNCTION__))
3036 "Cannot SCEV check stride or overflow when optimizing for size")(static_cast <bool> (!(SCEVCheckBlock->getParent()->
hasOptSize() || (OptForSizeBasedOnProfile && Cost->
Hints->getForce() != LoopVectorizeHints::FK_Enabled)) &&
"Cannot SCEV check stride or overflow when optimizing for size"
) ? void (0) : __assert_fail ("!(SCEVCheckBlock->getParent()->hasOptSize() || (OptForSizeBasedOnProfile && Cost->Hints->getForce() != LoopVectorizeHints::FK_Enabled)) && \"Cannot SCEV check stride or overflow when optimizing for size\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3036, __extension__
__PRETTY_FUNCTION__))
;
3037
3038
3039 // Update dominator only if this is first RT check.
3040 if (LoopBypassBlocks.empty()) {
3041 DT->changeImmediateDominator(Bypass, SCEVCheckBlock);
3042 if (!Cost->requiresScalarEpilogue(VF))
3043 // If there is an epilogue which must run, there's no edge from the
3044 // middle block to exit blocks and thus no need to update the immediate
3045 // dominator of the exit blocks.
3046 DT->changeImmediateDominator(LoopExitBlock, SCEVCheckBlock);
3047 }
3048
3049 LoopBypassBlocks.push_back(SCEVCheckBlock);
3050 AddedSafetyChecks = true;
3051 return SCEVCheckBlock;
3052}
3053
3054BasicBlock *InnerLoopVectorizer::emitMemRuntimeChecks(Loop *L,
3055 BasicBlock *Bypass) {
3056 // VPlan-native path does not do any analysis for runtime checks currently.
3057 if (EnableVPlanNativePath)
3058 return nullptr;
3059
3060 BasicBlock *const MemCheckBlock =
3061 RTChecks.emitMemRuntimeChecks(L, Bypass, LoopVectorPreHeader);
3062
3063 // Check if we generated code that checks in runtime if arrays overlap. We put
3064 // the checks into a separate block to make the more common case of few
3065 // elements faster.
3066 if (!MemCheckBlock)
3067 return nullptr;
3068
3069 if (MemCheckBlock->getParent()->hasOptSize() || OptForSizeBasedOnProfile) {
3070 assert(Cost->Hints->getForce() == LoopVectorizeHints::FK_Enabled &&(static_cast <bool> (Cost->Hints->getForce() == LoopVectorizeHints
::FK_Enabled && "Cannot emit memory checks when optimizing for size, unless forced "
"to vectorize.") ? void (0) : __assert_fail ("Cost->Hints->getForce() == LoopVectorizeHints::FK_Enabled && \"Cannot emit memory checks when optimizing for size, unless forced \" \"to vectorize.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3072, __extension__
__PRETTY_FUNCTION__))
3071 "Cannot emit memory checks when optimizing for size, unless forced "(static_cast <bool> (Cost->Hints->getForce() == LoopVectorizeHints
::FK_Enabled && "Cannot emit memory checks when optimizing for size, unless forced "
"to vectorize.") ? void (0) : __assert_fail ("Cost->Hints->getForce() == LoopVectorizeHints::FK_Enabled && \"Cannot emit memory checks when optimizing for size, unless forced \" \"to vectorize.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3072, __extension__
__PRETTY_FUNCTION__))
3072 "to vectorize.")(static_cast <bool> (Cost->Hints->getForce() == LoopVectorizeHints
::FK_Enabled && "Cannot emit memory checks when optimizing for size, unless forced "
"to vectorize.") ? void (0) : __assert_fail ("Cost->Hints->getForce() == LoopVectorizeHints::FK_Enabled && \"Cannot emit memory checks when optimizing for size, unless forced \" \"to vectorize.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3072, __extension__
__PRETTY_FUNCTION__))
;
3073 ORE->emit([&]() {
3074 return OptimizationRemarkAnalysis(DEBUG_TYPE"loop-vectorize", "VectorizationCodeSize",
3075 L->getStartLoc(), L->getHeader())
3076 << "Code-size may be reduced by not forcing "
3077 "vectorization, or by source-code modifications "
3078 "eliminating the need for runtime checks "
3079 "(e.g., adding 'restrict').";
3080 });
3081 }
3082
3083 LoopBypassBlocks.push_back(MemCheckBlock);
3084
3085 AddedSafetyChecks = true;
3086
3087 // We currently don't use LoopVersioning for the actual loop cloning but we
3088 // still use it to add the noalias metadata.
3089 LVer = std::make_unique<LoopVersioning>(
3090 *Legal->getLAI(),
3091 Legal->getLAI()->getRuntimePointerChecking()->getChecks(), OrigLoop, LI,
3092 DT, PSE.getSE());
3093 LVer->prepareNoAliasMetadata();
3094 return MemCheckBlock;
3095}
3096
3097Loop *InnerLoopVectorizer::createVectorLoopSkeleton(StringRef Prefix) {
3098 LoopScalarBody = OrigLoop->getHeader();
3099 LoopVectorPreHeader = OrigLoop->getLoopPreheader();
3100 assert(LoopVectorPreHeader && "Invalid loop structure")(static_cast <bool> (LoopVectorPreHeader && "Invalid loop structure"
) ? void (0) : __assert_fail ("LoopVectorPreHeader && \"Invalid loop structure\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3100, __extension__
__PRETTY_FUNCTION__))
;
3101 LoopExitBlock = OrigLoop->getUniqueExitBlock(); // may be nullptr
3102 assert((LoopExitBlock || Cost->requiresScalarEpilogue(VF)) &&(static_cast <bool> ((LoopExitBlock || Cost->requiresScalarEpilogue
(VF)) && "multiple exit loop without required epilogue?"
) ? void (0) : __assert_fail ("(LoopExitBlock || Cost->requiresScalarEpilogue(VF)) && \"multiple exit loop without required epilogue?\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3103, __extension__
__PRETTY_FUNCTION__))
3103 "multiple exit loop without required epilogue?")(static_cast <bool> ((LoopExitBlock || Cost->requiresScalarEpilogue
(VF)) && "multiple exit loop without required epilogue?"
) ? void (0) : __assert_fail ("(LoopExitBlock || Cost->requiresScalarEpilogue(VF)) && \"multiple exit loop without required epilogue?\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3103, __extension__
__PRETTY_FUNCTION__))
;
3104
3105 LoopMiddleBlock =
3106 SplitBlock(LoopVectorPreHeader, LoopVectorPreHeader->getTerminator(), DT,
3107 LI, nullptr, Twine(Prefix) + "middle.block");
3108 LoopScalarPreHeader =
3109 SplitBlock(LoopMiddleBlock, LoopMiddleBlock->getTerminator(), DT, LI,
3110 nullptr, Twine(Prefix) + "scalar.ph");
3111
3112 auto *ScalarLatchTerm = OrigLoop->getLoopLatch()->getTerminator();
3113
3114 // Set up the middle block terminator. Two cases:
3115 // 1) If we know that we must execute the scalar epilogue, emit an
3116 // unconditional branch.
3117 // 2) Otherwise, we must have a single unique exit block (due to how we
3118 // implement the multiple exit case). In this case, set up a conditonal
3119 // branch from the middle block to the loop scalar preheader, and the
3120 // exit block. completeLoopSkeleton will update the condition to use an
3121 // iteration check, if required to decide whether to execute the remainder.
3122 BranchInst *BrInst = Cost->requiresScalarEpilogue(VF) ?
3123 BranchInst::Create(LoopScalarPreHeader) :
3124 BranchInst::Create(LoopExitBlock, LoopScalarPreHeader,
3125 Builder.getTrue());
3126 BrInst->setDebugLoc(ScalarLatchTerm->getDebugLoc());
3127 ReplaceInstWithInst(LoopMiddleBlock->getTerminator(), BrInst);
3128
3129 // We intentionally don't let SplitBlock to update LoopInfo since
3130 // LoopVectorBody should belong to another loop than LoopVectorPreHeader.
3131 // LoopVectorBody is explicitly added to the correct place few lines later.
3132 BasicBlock *LoopVectorBody =
3133 SplitBlock(LoopVectorPreHeader, LoopVectorPreHeader->getTerminator(), DT,
3134 nullptr, nullptr, Twine(Prefix) + "vector.body");
3135
3136 // Update dominator for loop exit.
3137 if (!Cost->requiresScalarEpilogue(VF))
3138 // If there is an epilogue which must run, there's no edge from the
3139 // middle block to exit blocks and thus no need to update the immediate
3140 // dominator of the exit blocks.
3141 DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock);
3142
3143 // Create and register the new vector loop.
3144 Loop *Lp = LI->AllocateLoop();
3145 Loop *ParentLoop = OrigLoop->getParentLoop();
3146
3147 // Insert the new loop into the loop nest and register the new basic blocks
3148 // before calling any utilities such as SCEV that require valid LoopInfo.
3149 if (ParentLoop) {
3150 ParentLoop->addChildLoop(Lp);
3151 } else {
3152 LI->addTopLevelLoop(Lp);
3153 }
3154 Lp->addBasicBlockToLoop(LoopVectorBody, *LI);
3155 return Lp;
3156}
3157
3158void InnerLoopVectorizer::createInductionResumeValues(
3159 Loop *L, std::pair<BasicBlock *, Value *> AdditionalBypass) {
3160 assert(((AdditionalBypass.first && AdditionalBypass.second) ||(static_cast <bool> (((AdditionalBypass.first &&
AdditionalBypass.second) || (!AdditionalBypass.first &&
!AdditionalBypass.second)) && "Inconsistent information about additional bypass."
) ? void (0) : __assert_fail ("((AdditionalBypass.first && AdditionalBypass.second) || (!AdditionalBypass.first && !AdditionalBypass.second)) && \"Inconsistent information about additional bypass.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3162, __extension__
__PRETTY_FUNCTION__))
3161 (!AdditionalBypass.first && !AdditionalBypass.second)) &&(static_cast <bool> (((AdditionalBypass.first &&
AdditionalBypass.second) || (!AdditionalBypass.first &&
!AdditionalBypass.second)) && "Inconsistent information about additional bypass."
) ? void (0) : __assert_fail ("((AdditionalBypass.first && AdditionalBypass.second) || (!AdditionalBypass.first && !AdditionalBypass.second)) && \"Inconsistent information about additional bypass.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3162, __extension__
__PRETTY_FUNCTION__))
3162 "Inconsistent information about additional bypass.")(static_cast <bool> (((AdditionalBypass.first &&
AdditionalBypass.second) || (!AdditionalBypass.first &&
!AdditionalBypass.second)) && "Inconsistent information about additional bypass."
) ? void (0) : __assert_fail ("((AdditionalBypass.first && AdditionalBypass.second) || (!AdditionalBypass.first && !AdditionalBypass.second)) && \"Inconsistent information about additional bypass.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3162, __extension__
__PRETTY_FUNCTION__))
;
3163
3164 Value *VectorTripCount = getOrCreateVectorTripCount(L);
3165 assert(VectorTripCount && L && "Expected valid arguments")(static_cast <bool> (VectorTripCount && L &&
"Expected valid arguments") ? void (0) : __assert_fail ("VectorTripCount && L && \"Expected valid arguments\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3165, __extension__
__PRETTY_FUNCTION__))
;
3166 // We are going to resume the execution of the scalar loop.
3167 // Go over all of the induction variables that we found and fix the
3168 // PHIs that are left in the scalar version of the loop.
3169 // The starting values of PHI nodes depend on the counter of the last
3170 // iteration in the vectorized loop.
3171 // If we come from a bypass edge then we need to start from the original
3172 // start value.
3173 Instruction *OldInduction = Legal->getPrimaryInduction();
3174 for (auto &InductionEntry : Legal->getInductionVars()) {
3175 PHINode *OrigPhi = InductionEntry.first;
3176 InductionDescriptor II = InductionEntry.second;
3177
3178 // Create phi nodes to merge from the backedge-taken check block.
3179 PHINode *BCResumeVal =
3180 PHINode::Create(OrigPhi->getType(), 3, "bc.resume.val",
3181 LoopScalarPreHeader->getTerminator());
3182 // Copy original phi DL over to the new one.
3183 BCResumeVal->setDebugLoc(OrigPhi->getDebugLoc());
3184 Value *&EndValue = IVEndValues[OrigPhi];
3185 Value *EndValueFromAdditionalBypass = AdditionalBypass.second;
3186 if (OrigPhi == OldInduction) {
3187 // We know what the end value is.
3188 EndValue = VectorTripCount;
3189 } else {
3190 IRBuilder<> B(L->getLoopPreheader()->getTerminator());
3191
3192 // Fast-math-flags propagate from the original induction instruction.
3193 if (II.getInductionBinOp() && isa<FPMathOperator>(II.getInductionBinOp()))
3194 B.setFastMathFlags(II.getInductionBinOp()->getFastMathFlags());
3195
3196 Type *StepType = II.getStep()->getType();
3197 Instruction::CastOps CastOp =
3198 CastInst::getCastOpcode(VectorTripCount, true, StepType, true);
3199 Value *CRD = B.CreateCast(CastOp, VectorTripCount, StepType, "cast.crd");
3200 Value *Step =
3201 CreateStepValue(II.getStep(), *PSE.getSE(), &*B.GetInsertPoint());
3202 EndValue = emitTransformedIndex(B, CRD, II.getStartValue(), Step, II);
3203 EndValue->setName("ind.end");
3204
3205 // Compute the end value for the additional bypass (if applicable).
3206 if (AdditionalBypass.first) {
3207 B.SetInsertPoint(&(*AdditionalBypass.first->getFirstInsertionPt()));
3208 CastOp = CastInst::getCastOpcode(AdditionalBypass.second, true,
3209 StepType, true);
3210 Value *Step =
3211 CreateStepValue(II.getStep(), *PSE.getSE(), &*B.GetInsertPoint());
3212 CRD =
3213 B.CreateCast(CastOp, AdditionalBypass.second, StepType, "cast.crd");
3214 EndValueFromAdditionalBypass =
3215 emitTransformedIndex(B, CRD, II.getStartValue(), Step, II);
3216 EndValueFromAdditionalBypass->setName("ind.end");
3217 }
3218 }
3219 // The new PHI merges the original incoming value, in case of a bypass,
3220 // or the value at the end of the vectorized loop.
3221 BCResumeVal->addIncoming(EndValue, LoopMiddleBlock);
3222
3223 // Fix the scalar body counter (PHI node).
3224 // The old induction's phi node in the scalar body needs the truncated
3225 // value.
3226 for (BasicBlock *BB : LoopBypassBlocks)
3227 BCResumeVal->addIncoming(II.getStartValue(), BB);
3228
3229 if (AdditionalBypass.first)
3230 BCResumeVal->setIncomingValueForBlock(AdditionalBypass.first,
3231 EndValueFromAdditionalBypass);
3232
3233 OrigPhi->setIncomingValueForBlock(LoopScalarPreHeader, BCResumeVal);
3234 }
3235}
3236
3237BasicBlock *InnerLoopVectorizer::completeLoopSkeleton(Loop *L,
3238 MDNode *OrigLoopID) {
3239 assert(L && "Expected valid loop.")(static_cast <bool> (L && "Expected valid loop."
) ? void (0) : __assert_fail ("L && \"Expected valid loop.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3239, __extension__
__PRETTY_FUNCTION__))
;
3240
3241 // The trip counts should be cached by now.
3242 Value *Count = getOrCreateTripCount(L);
3243 Value *VectorTripCount = getOrCreateVectorTripCount(L);
3244
3245 auto *ScalarLatchTerm = OrigLoop->getLoopLatch()->getTerminator();
3246
3247 // Add a check in the middle block to see if we have completed
3248 // all of the iterations in the first vector loop. Three cases:
3249 // 1) If we require a scalar epilogue, there is no conditional branch as
3250 // we unconditionally branch to the scalar preheader. Do nothing.
3251 // 2) If (N - N%VF) == N, then we *don't* need to run the remainder.
3252 // Thus if tail is to be folded, we know we don't need to run the
3253 // remainder and we can use the previous value for the condition (true).
3254 // 3) Otherwise, construct a runtime check.
3255 if (!Cost->requiresScalarEpilogue(VF) && !Cost->foldTailByMasking()) {
3256 Instruction *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ,
3257 Count, VectorTripCount, "cmp.n",
3258 LoopMiddleBlock->getTerminator());
3259
3260 // Here we use the same DebugLoc as the scalar loop latch terminator instead
3261 // of the corresponding compare because they may have ended up with
3262 // different line numbers and we want to avoid awkward line stepping while
3263 // debugging. Eg. if the compare has got a line number inside the loop.
3264 CmpN->setDebugLoc(ScalarLatchTerm->getDebugLoc());
3265 cast<BranchInst>(LoopMiddleBlock->getTerminator())->setCondition(CmpN);
3266 }
3267
3268 // Get ready to start creating new instructions into the vectorized body.
3269 assert(LoopVectorPreHeader == L->getLoopPreheader() &&(static_cast <bool> (LoopVectorPreHeader == L->getLoopPreheader
() && "Inconsistent vector loop preheader") ? void (0
) : __assert_fail ("LoopVectorPreHeader == L->getLoopPreheader() && \"Inconsistent vector loop preheader\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3270, __extension__
__PRETTY_FUNCTION__))
3270 "Inconsistent vector loop preheader")(static_cast <bool> (LoopVectorPreHeader == L->getLoopPreheader
() && "Inconsistent vector loop preheader") ? void (0
) : __assert_fail ("LoopVectorPreHeader == L->getLoopPreheader() && \"Inconsistent vector loop preheader\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3270, __extension__
__PRETTY_FUNCTION__))
;
3271
3272#ifdef EXPENSIVE_CHECKS
3273 assert(DT->verify(DominatorTree::VerificationLevel::Fast))(static_cast <bool> (DT->verify(DominatorTree::VerificationLevel
::Fast)) ? void (0) : __assert_fail ("DT->verify(DominatorTree::VerificationLevel::Fast)"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3273, __extension__
__PRETTY_FUNCTION__))
;
3274 LI->verify(*DT);
3275#endif
3276
3277 return LoopVectorPreHeader;
3278}
3279
3280std::pair<BasicBlock *, Value *>
3281InnerLoopVectorizer::createVectorizedLoopSkeleton() {
3282 /*
3283 In this function we generate a new loop. The new loop will contain
3284 the vectorized instructions while the old loop will continue to run the
3285 scalar remainder.
3286
3287 [ ] <-- loop iteration number check.
3288 / |
3289 / v
3290 | [ ] <-- vector loop bypass (may consist of multiple blocks).
3291 | / |
3292 | / v
3293 || [ ] <-- vector pre header.
3294 |/ |
3295 | v
3296 | [ ] \
3297 | [ ]_| <-- vector loop.
3298 | |
3299 | v
3300 \ -[ ] <--- middle-block.
3301 \/ |
3302 /\ v
3303 | ->[ ] <--- new preheader.
3304 | |
3305 (opt) v <-- edge from middle to exit iff epilogue is not required.
3306 | [ ] \
3307 | [ ]_| <-- old scalar loop to handle remainder (scalar epilogue).
3308 \ |
3309 \ v
3310 >[ ] <-- exit block(s).
3311 ...
3312 */
3313
3314 // Get the metadata of the original loop before it gets modified.
3315 MDNode *OrigLoopID = OrigLoop->getLoopID();
3316
3317 // Workaround! Compute the trip count of the original loop and cache it
3318 // before we start modifying the CFG. This code has a systemic problem
3319 // wherein it tries to run analysis over partially constructed IR; this is
3320 // wrong, and not simply for SCEV. The trip count of the original loop
3321 // simply happens to be prone to hitting this in practice. In theory, we
3322 // can hit the same issue for any SCEV, or ValueTracking query done during
3323 // mutation. See PR49900.
3324 getOrCreateTripCount(OrigLoop);
3325
3326 // Create an empty vector loop, and prepare basic blocks for the runtime
3327 // checks.
3328 Loop *Lp = createVectorLoopSkeleton("");
3329
3330 // Now, compare the new count to zero. If it is zero skip the vector loop and
3331 // jump to the scalar loop. This check also covers the case where the
3332 // backedge-taken count is uint##_max: adding one to it will overflow leading
3333 // to an incorrect trip count of zero. In this (rare) case we will also jump
3334 // to the scalar loop.
3335 emitMinimumIterationCountCheck(Lp, LoopScalarPreHeader);
3336
3337 // Generate the code to check any assumptions that we've made for SCEV
3338 // expressions.
3339 emitSCEVChecks(LoopScalarPreHeader);
3340
3341 // Generate the code that checks in runtime if arrays overlap. We put the
3342 // checks into a separate block to make the more common case of few elements
3343 // faster.
3344 emitMemRuntimeChecks(Lp, LoopScalarPreHeader);
3345
3346 createHeaderBranch(Lp);
3347
3348 // Emit phis for the new starting index of the scalar loop.
3349 createInductionResumeValues(Lp);
3350
3351 return {completeLoopSkeleton(Lp, OrigLoopID), nullptr};
3352}
3353
3354// Fix up external users of the induction variable. At this point, we are
3355// in LCSSA form, with all external PHIs that use the IV having one input value,
3356// coming from the remainder loop. We need those PHIs to also have a correct
3357// value for the IV when arriving directly from the middle block.
3358void InnerLoopVectorizer::fixupIVUsers(PHINode *OrigPhi,
3359 const InductionDescriptor &II,
3360 Value *CountRoundDown, Value *EndValue,
3361 BasicBlock *MiddleBlock,
3362 BasicBlock *VectorHeader) {
3363 // There are two kinds of external IV usages - those that use the value
3364 // computed in the last iteration (the PHI) and those that use the penultimate
3365 // value (the value that feeds into the phi from the loop latch).
3366 // We allow both, but they, obviously, have different values.
3367
3368 assert(OrigLoop->getUniqueExitBlock() && "Expected a single exit block")(static_cast <bool> (OrigLoop->getUniqueExitBlock() &&
"Expected a single exit block") ? void (0) : __assert_fail (
"OrigLoop->getUniqueExitBlock() && \"Expected a single exit block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3368, __extension__
__PRETTY_FUNCTION__))
;
3369
3370 DenseMap<Value *, Value *> MissingVals;
3371
3372 // An external user of the last iteration's value should see the value that
3373 // the remainder loop uses to initialize its own IV.
3374 Value *PostInc = OrigPhi->getIncomingValueForBlock(OrigLoop->getLoopLatch());
3375 for (User *U : PostInc->users()) {
3376 Instruction *UI = cast<Instruction>(U);
3377 if (!OrigLoop->contains(UI)) {
3378 assert(isa<PHINode>(UI) && "Expected LCSSA form")(static_cast <bool> (isa<PHINode>(UI) && "Expected LCSSA form"
) ? void (0) : __assert_fail ("isa<PHINode>(UI) && \"Expected LCSSA form\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3378, __extension__
__PRETTY_FUNCTION__))
;
3379 MissingVals[UI] = EndValue;
3380 }
3381 }
3382
3383 // An external user of the penultimate value need to see EndValue - Step.
3384 // The simplest way to get this is to recompute it from the constituent SCEVs,
3385 // that is Start + (Step * (CRD - 1)).
3386 for (User *U : OrigPhi->users()) {
3387 auto *UI = cast<Instruction>(U);
3388 if (!OrigLoop->contains(UI)) {
3389 assert(isa<PHINode>(UI) && "Expected LCSSA form")(static_cast <bool> (isa<PHINode>(UI) && "Expected LCSSA form"
) ? void (0) : __assert_fail ("isa<PHINode>(UI) && \"Expected LCSSA form\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3389, __extension__
__PRETTY_FUNCTION__))
;
3390
3391 IRBuilder<> B(MiddleBlock->getTerminator());
3392
3393 // Fast-math-flags propagate from the original induction instruction.
3394 if (II.getInductionBinOp() && isa<FPMathOperator>(II.getInductionBinOp()))
3395 B.setFastMathFlags(II.getInductionBinOp()->getFastMathFlags());
3396
3397 Value *CountMinusOne = B.CreateSub(
3398 CountRoundDown, ConstantInt::get(CountRoundDown->getType(), 1));
3399 Value *CMO =
3400 !II.getStep()->getType()->isIntegerTy()
3401 ? B.CreateCast(Instruction::SIToFP, CountMinusOne,
3402 II.getStep()->getType())
3403 : B.CreateSExtOrTrunc(CountMinusOne, II.getStep()->getType());
3404 CMO->setName("cast.cmo");
3405
3406 Value *Step = CreateStepValue(II.getStep(), *PSE.getSE(),
3407 VectorHeader->getTerminator());
3408 Value *Escape =
3409 emitTransformedIndex(B, CMO, II.getStartValue(), Step, II);
3410 Escape->setName("ind.escape");
3411 MissingVals[UI] = Escape;
3412 }
3413 }
3414
3415 for (auto &I : MissingVals) {
3416 PHINode *PHI = cast<PHINode>(I.first);
3417 // One corner case we have to handle is two IVs "chasing" each-other,
3418 // that is %IV2 = phi [...], [ %IV1, %latch ]
3419 // In this case, if IV1 has an external use, we need to avoid adding both
3420 // "last value of IV1" and "penultimate value of IV2". So, verify that we
3421 // don't already have an incoming value for the middle block.
3422 if (PHI->getBasicBlockIndex(MiddleBlock) == -1)
3423 PHI->addIncoming(I.second, MiddleBlock);
3424 }
3425}
3426
3427namespace {
3428
3429struct CSEDenseMapInfo {
3430 static bool canHandle(const Instruction *I) {
3431 return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) ||
3432 isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I);
3433 }
3434
3435 static inline Instruction *getEmptyKey() {
3436 return DenseMapInfo<Instruction *>::getEmptyKey();
3437 }
3438
3439 static inline Instruction *getTombstoneKey() {
3440 return DenseMapInfo<Instruction *>::getTombstoneKey();
3441 }
3442
3443 static unsigned getHashValue(const Instruction *I) {
3444 assert(canHandle(I) && "Unknown instruction!")(static_cast <bool> (canHandle(I) && "Unknown instruction!"
) ? void (0) : __assert_fail ("canHandle(I) && \"Unknown instruction!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3444, __extension__
__PRETTY_FUNCTION__))
;
3445 return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(),
3446 I->value_op_end()));
3447 }
3448
3449 static bool isEqual(const Instruction *LHS, const Instruction *RHS) {
3450 if (LHS == getEmptyKey() || RHS == getEmptyKey() ||
3451 LHS == getTombstoneKey() || RHS == getTombstoneKey())
3452 return LHS == RHS;
3453 return LHS->isIdenticalTo(RHS);
3454 }
3455};
3456
3457} // end anonymous namespace
3458
3459///Perform cse of induction variable instructions.
3460static void cse(BasicBlock *BB) {
3461 // Perform simple cse.
3462 SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap;
3463 for (Instruction &In : llvm::make_early_inc_range(*BB)) {
3464 if (!CSEDenseMapInfo::canHandle(&In))
3465 continue;
3466
3467 // Check if we can replace this instruction with any of the
3468 // visited instructions.
3469 if (Instruction *V = CSEMap.lookup(&In)) {
3470 In.replaceAllUsesWith(V);
3471 In.eraseFromParent();
3472 continue;
3473 }
3474
3475 CSEMap[&In] = &In;
3476 }
3477}
3478
3479InstructionCost
3480LoopVectorizationCostModel::getVectorCallCost(CallInst *CI, ElementCount VF,
3481 bool &NeedToScalarize) const {
3482 Function *F = CI->getCalledFunction();
3483 Type *ScalarRetTy = CI->getType();
3484 SmallVector<Type *, 4> Tys, ScalarTys;
3485 for (auto &ArgOp : CI->args())
3486 ScalarTys.push_back(ArgOp->getType());
3487
3488 // Estimate cost of scalarized vector call. The source operands are assumed
3489 // to be vectors, so we need to extract individual elements from there,
3490 // execute VF scalar calls, and then gather the result into the vector return
3491 // value.
3492 InstructionCost ScalarCallCost =
3493 TTI.getCallInstrCost(F, ScalarRetTy, ScalarTys, TTI::TCK_RecipThroughput);
3494 if (VF.isScalar())
3495 return ScalarCallCost;
3496
3497 // Compute corresponding vector type for return value and arguments.
3498 Type *RetTy = ToVectorTy(ScalarRetTy, VF);
3499 for (Type *ScalarTy : ScalarTys)
3500 Tys.push_back(ToVectorTy(ScalarTy, VF));
3501
3502 // Compute costs of unpacking argument values for the scalar calls and
3503 // packing the return values to a vector.
3504 InstructionCost ScalarizationCost = getScalarizationOverhead(CI, VF);
3505
3506 InstructionCost Cost =
3507 ScalarCallCost * VF.getKnownMinValue() + ScalarizationCost;
3508
3509 // If we can't emit a vector call for this function, then the currently found
3510 // cost is the cost we need to return.
3511 NeedToScalarize = true;
3512 VFShape Shape = VFShape::get(*CI, VF, false /*HasGlobalPred*/);
3513 Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape);
3514
3515 if (!TLI || CI->isNoBuiltin() || !VecFunc)
3516 return Cost;
3517
3518 // If the corresponding vector cost is cheaper, return its cost.
3519 InstructionCost VectorCallCost =
3520 TTI.getCallInstrCost(nullptr, RetTy, Tys, TTI::TCK_RecipThroughput);
3521 if (VectorCallCost < Cost) {
3522 NeedToScalarize = false;
3523 Cost = VectorCallCost;
3524 }
3525 return Cost;
3526}
3527
3528static Type *MaybeVectorizeType(Type *Elt, ElementCount VF) {
3529 if (VF.isScalar() || (!Elt->isIntOrPtrTy() && !Elt->isFloatingPointTy()))
3530 return Elt;
3531 return VectorType::get(Elt, VF);
3532}
3533
3534InstructionCost
3535LoopVectorizationCostModel::getVectorIntrinsicCost(CallInst *CI,
3536 ElementCount VF) const {
3537 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
3538 assert(ID && "Expected intrinsic call!")(static_cast <bool> (ID && "Expected intrinsic call!"
) ? void (0) : __assert_fail ("ID && \"Expected intrinsic call!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3538, __extension__
__PRETTY_FUNCTION__))
;
3539 Type *RetTy = MaybeVectorizeType(CI->getType(), VF);
3540 FastMathFlags FMF;
3541 if (auto *FPMO = dyn_cast<FPMathOperator>(CI))
3542 FMF = FPMO->getFastMathFlags();
3543
3544 SmallVector<const Value *> Arguments(CI->args());
3545 FunctionType *FTy = CI->getCalledFunction()->getFunctionType();
3546 SmallVector<Type *> ParamTys;
3547 std::transform(FTy->param_begin(), FTy->param_end(),
3548 std::back_inserter(ParamTys),
3549 [&](Type *Ty) { return MaybeVectorizeType(Ty, VF); });
3550
3551 IntrinsicCostAttributes CostAttrs(ID, RetTy, Arguments, ParamTys, FMF,
3552 dyn_cast<IntrinsicInst>(CI));
3553 return TTI.getIntrinsicInstrCost(CostAttrs,
3554 TargetTransformInfo::TCK_RecipThroughput);
3555}
3556
3557static Type *smallestIntegerVectorType(Type *T1, Type *T2) {
3558 auto *I1 = cast<IntegerType>(cast<VectorType>(T1)->getElementType());
3559 auto *I2 = cast<IntegerType>(cast<VectorType>(T2)->getElementType());
3560 return I1->getBitWidth() < I2->getBitWidth() ? T1 : T2;
3561}
3562
3563static Type *largestIntegerVectorType(Type *T1, Type *T2) {
3564 auto *I1 = cast<IntegerType>(cast<VectorType>(T1)->getElementType());
3565 auto *I2 = cast<IntegerType>(cast<VectorType>(T2)->getElementType());
3566 return I1->getBitWidth() > I2->getBitWidth() ? T1 : T2;
3567}
3568
3569void InnerLoopVectorizer::truncateToMinimalBitwidths(VPTransformState &State) {
3570 // For every instruction `I` in MinBWs, truncate the operands, create a
3571 // truncated version of `I` and reextend its result. InstCombine runs
3572 // later and will remove any ext/trunc pairs.
3573 SmallPtrSet<Value *, 4> Erased;
3574 for (const auto &KV : Cost->getMinimalBitwidths()) {
3575 // If the value wasn't vectorized, we must maintain the original scalar
3576 // type. The absence of the value from State indicates that it
3577 // wasn't vectorized.
3578 // FIXME: Should not rely on getVPValue at this point.
3579 VPValue *Def = State.Plan->getVPValue(KV.first, true);
3580 if (!State.hasAnyVectorValue(Def))
3581 continue;
3582 for (unsigned Part = 0; Part < UF; ++Part) {
3583 Value *I = State.get(Def, Part);
3584 if (Erased.count(I) || I->use_empty() || !isa<Instruction>(I))
3585 continue;
3586 Type *OriginalTy = I->getType();
3587 Type *ScalarTruncatedTy =
3588 IntegerType::get(OriginalTy->getContext(), KV.second);
3589 auto *TruncatedTy = VectorType::get(
3590 ScalarTruncatedTy, cast<VectorType>(OriginalTy)->getElementCount());
3591 if (TruncatedTy == OriginalTy)
3592 continue;
3593
3594 IRBuilder<> B(cast<Instruction>(I));
3595 auto ShrinkOperand = [&](Value *V) -> Value * {
3596 if (auto *ZI = dyn_cast<ZExtInst>(V))
3597 if (ZI->getSrcTy() == TruncatedTy)
3598 return ZI->getOperand(0);
3599 return B.CreateZExtOrTrunc(V, TruncatedTy);
3600 };
3601
3602 // The actual instruction modification depends on the instruction type,
3603 // unfortunately.
3604 Value *NewI = nullptr;
3605 if (auto *BO = dyn_cast<BinaryOperator>(I)) {
3606 NewI = B.CreateBinOp(BO->getOpcode(), ShrinkOperand(BO->getOperand(0)),
3607 ShrinkOperand(BO->getOperand(1)));
3608
3609 // Any wrapping introduced by shrinking this operation shouldn't be
3610 // considered undefined behavior. So, we can't unconditionally copy
3611 // arithmetic wrapping flags to NewI.
3612 cast<BinaryOperator>(NewI)->copyIRFlags(I, /*IncludeWrapFlags=*/false);
3613 } else if (auto *CI = dyn_cast<ICmpInst>(I)) {
3614 NewI =
3615 B.CreateICmp(CI->getPredicate(), ShrinkOperand(CI->getOperand(0)),
3616 ShrinkOperand(CI->getOperand(1)));
3617 } else if (auto *SI = dyn_cast<SelectInst>(I)) {
3618 NewI = B.CreateSelect(SI->getCondition(),
3619 ShrinkOperand(SI->getTrueValue()),
3620 ShrinkOperand(SI->getFalseValue()));
3621 } else if (auto *CI = dyn_cast<CastInst>(I)) {
3622 switch (CI->getOpcode()) {
3623 default:
3624 llvm_unreachable("Unhandled cast!")::llvm::llvm_unreachable_internal("Unhandled cast!", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 3624)
;
3625 case Instruction::Trunc:
3626 NewI = ShrinkOperand(CI->getOperand(0));
3627 break;
3628 case Instruction::SExt:
3629 NewI = B.CreateSExtOrTrunc(
3630 CI->getOperand(0),
3631 smallestIntegerVectorType(OriginalTy, TruncatedTy));
3632 break;
3633 case Instruction::ZExt:
3634 NewI = B.CreateZExtOrTrunc(
3635 CI->getOperand(0),
3636 smallestIntegerVectorType(OriginalTy, TruncatedTy));
3637 break;
3638 }
3639 } else if (auto *SI = dyn_cast<ShuffleVectorInst>(I)) {
3640 auto Elements0 =
3641 cast<VectorType>(SI->getOperand(0)->getType())->getElementCount();
3642 auto *O0 = B.CreateZExtOrTrunc(
3643 SI->getOperand(0), VectorType::get(ScalarTruncatedTy, Elements0));
3644 auto Elements1 =
3645 cast<VectorType>(SI->getOperand(1)->getType())->getElementCount();
3646 auto *O1 = B.CreateZExtOrTrunc(
3647 SI->getOperand(1), VectorType::get(ScalarTruncatedTy, Elements1));
3648
3649 NewI = B.CreateShuffleVector(O0, O1, SI->getShuffleMask());
3650 } else if (isa<LoadInst>(I) || isa<PHINode>(I)) {
3651 // Don't do anything with the operands, just extend the result.
3652 continue;
3653 } else if (auto *IE = dyn_cast<InsertElementInst>(I)) {
3654 auto Elements =
3655 cast<VectorType>(IE->getOperand(0)->getType())->getElementCount();
3656 auto *O0 = B.CreateZExtOrTrunc(
3657 IE->getOperand(0), VectorType::get(ScalarTruncatedTy, Elements));
3658 auto *O1 = B.CreateZExtOrTrunc(IE->getOperand(1), ScalarTruncatedTy);
3659 NewI = B.CreateInsertElement(O0, O1, IE->getOperand(2));
3660 } else if (auto *EE = dyn_cast<ExtractElementInst>(I)) {
3661 auto Elements =
3662 cast<VectorType>(EE->getOperand(0)->getType())->getElementCount();
3663 auto *O0 = B.CreateZExtOrTrunc(
3664 EE->getOperand(0), VectorType::get(ScalarTruncatedTy, Elements));
3665 NewI = B.CreateExtractElement(O0, EE->getOperand(2));
3666 } else {
3667 // If we don't know what to do, be conservative and don't do anything.
3668 continue;
3669 }
3670
3671 // Lastly, extend the result.
3672 NewI->takeName(cast<Instruction>(I));
3673 Value *Res = B.CreateZExtOrTrunc(NewI, OriginalTy);
3674 I->replaceAllUsesWith(Res);
3675 cast<Instruction>(I)->eraseFromParent();
3676 Erased.insert(I);
3677 State.reset(Def, Res, Part);
3678 }
3679 }
3680
3681 // We'll have created a bunch of ZExts that are now parentless. Clean up.
3682 for (const auto &KV : Cost->getMinimalBitwidths()) {
3683 // If the value wasn't vectorized, we must maintain the original scalar
3684 // type. The absence of the value from State indicates that it
3685 // wasn't vectorized.
3686 // FIXME: Should not rely on getVPValue at this point.
3687 VPValue *Def = State.Plan->getVPValue(KV.first, true);
3688 if (!State.hasAnyVectorValue(Def))
3689 continue;
3690 for (unsigned Part = 0; Part < UF; ++Part) {
3691 Value *I = State.get(Def, Part);
3692 ZExtInst *Inst = dyn_cast<ZExtInst>(I);
3693 if (Inst && Inst->use_empty()) {
3694 Value *NewI = Inst->getOperand(0);
3695 Inst->eraseFromParent();
3696 State.reset(Def, NewI, Part);
3697 }
3698 }
3699 }
3700}
3701
3702void InnerLoopVectorizer::fixVectorizedLoop(VPTransformState &State) {
3703 // Insert truncates and extends for any truncated instructions as hints to
3704 // InstCombine.
3705 if (VF.isVector())
3706 truncateToMinimalBitwidths(State);
3707
3708 // Fix widened non-induction PHIs by setting up the PHI operands.
3709 if (OrigPHIsToFix.size()) {
3710 assert(EnableVPlanNativePath &&(static_cast <bool> (EnableVPlanNativePath && "Unexpected non-induction PHIs for fixup in non VPlan-native path"
) ? void (0) : __assert_fail ("EnableVPlanNativePath && \"Unexpected non-induction PHIs for fixup in non VPlan-native path\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3711, __extension__
__PRETTY_FUNCTION__))
3711 "Unexpected non-induction PHIs for fixup in non VPlan-native path")(static_cast <bool> (EnableVPlanNativePath && "Unexpected non-induction PHIs for fixup in non VPlan-native path"
) ? void (0) : __assert_fail ("EnableVPlanNativePath && \"Unexpected non-induction PHIs for fixup in non VPlan-native path\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3711, __extension__
__PRETTY_FUNCTION__))
;
3712 fixNonInductionPHIs(State);
3713 }
3714
3715 // At this point every instruction in the original loop is widened to a
3716 // vector form. Now we need to fix the recurrences in the loop. These PHI
3717 // nodes are currently empty because we did not want to introduce cycles.
3718 // This is the second stage of vectorizing recurrences.
3719 fixCrossIterationPHIs(State);
3720
3721 // Forget the original basic block.
3722 PSE.getSE()->forgetLoop(OrigLoop);
3723
3724 Loop *VectorLoop = LI->getLoopFor(State.CFG.PrevBB);
3725 // If we inserted an edge from the middle block to the unique exit block,
3726 // update uses outside the loop (phis) to account for the newly inserted
3727 // edge.
3728 if (!Cost->requiresScalarEpilogue(VF)) {
3729 // Fix-up external users of the induction variables.
3730 for (auto &Entry : Legal->getInductionVars())
3731 fixupIVUsers(
3732 Entry.first, Entry.second, getOrCreateVectorTripCount(VectorLoop),
3733 IVEndValues[Entry.first], LoopMiddleBlock, VectorLoop->getHeader());
3734
3735 fixLCSSAPHIs(State);
3736 }
3737
3738 for (Instruction *PI : PredicatedInstructions)
3739 sinkScalarOperands(&*PI);
3740
3741 // Remove redundant induction instructions.
3742 cse(VectorLoop->getHeader());
3743
3744 // Set/update profile weights for the vector and remainder loops as original
3745 // loop iterations are now distributed among them. Note that original loop
3746 // represented by LoopScalarBody becomes remainder loop after vectorization.
3747 //
3748 // For cases like foldTailByMasking() and requiresScalarEpiloque() we may
3749 // end up getting slightly roughened result but that should be OK since
3750 // profile is not inherently precise anyway. Note also possible bypass of
3751 // vector code caused by legality checks is ignored, assigning all the weight
3752 // to the vector loop, optimistically.
3753 //
3754 // For scalable vectorization we can't know at compile time how many iterations
3755 // of the loop are handled in one vector iteration, so instead assume a pessimistic
3756 // vscale of '1'.
3757 setProfileInfoAfterUnrolling(LI->getLoopFor(LoopScalarBody), VectorLoop,
3758 LI->getLoopFor(LoopScalarBody),
3759 VF.getKnownMinValue() * UF);
3760}
3761
3762void InnerLoopVectorizer::fixCrossIterationPHIs(VPTransformState &State) {
3763 // In order to support recurrences we need to be able to vectorize Phi nodes.
3764 // Phi nodes have cycles, so we need to vectorize them in two stages. This is
3765 // stage #2: We now need to fix the recurrences by adding incoming edges to
3766 // the currently empty PHI nodes. At this point every instruction in the
3767 // original loop is widened to a vector form so we can use them to construct
3768 // the incoming edges.
3769 VPBasicBlock *Header = State.Plan->getEntry()->getEntryBasicBlock();
3770 for (VPRecipeBase &R : Header->phis()) {
3771 if (auto *ReductionPhi = dyn_cast<VPReductionPHIRecipe>(&R))
3772 fixReduction(ReductionPhi, State);
3773 else if (auto *FOR = dyn_cast<VPFirstOrderRecurrencePHIRecipe>(&R))
3774 fixFirstOrderRecurrence(FOR, State);
3775 }
3776}
3777
3778void InnerLoopVectorizer::fixFirstOrderRecurrence(
3779 VPFirstOrderRecurrencePHIRecipe *PhiR, VPTransformState &State) {
3780 // This is the second phase of vectorizing first-order recurrences. An
3781 // overview of the transformation is described below. Suppose we have the
3782 // following loop.
3783 //
3784 // for (int i = 0; i < n; ++i)
3785 // b[i] = a[i] - a[i - 1];
3786 //
3787 // There is a first-order recurrence on "a". For this loop, the shorthand
3788 // scalar IR looks like:
3789 //
3790 // scalar.ph:
3791 // s_init = a[-1]
3792 // br scalar.body
3793 //
3794 // scalar.body:
3795 // i = phi [0, scalar.ph], [i+1, scalar.body]
3796 // s1 = phi [s_init, scalar.ph], [s2, scalar.body]
3797 // s2 = a[i]
3798 // b[i] = s2 - s1
3799 // br cond, scalar.body, ...
3800 //
3801 // In this example, s1 is a recurrence because it's value depends on the
3802 // previous iteration. In the first phase of vectorization, we created a
3803 // vector phi v1 for s1. We now complete the vectorization and produce the
3804 // shorthand vector IR shown below (for VF = 4, UF = 1).
3805 //
3806 // vector.ph:
3807 // v_init = vector(..., ..., ..., a[-1])
3808 // br vector.body
3809 //
3810 // vector.body
3811 // i = phi [0, vector.ph], [i+4, vector.body]
3812 // v1 = phi [v_init, vector.ph], [v2, vector.body]
3813 // v2 = a[i, i+1, i+2, i+3];
3814 // v3 = vector(v1(3), v2(0, 1, 2))
3815 // b[i, i+1, i+2, i+3] = v2 - v3
3816 // br cond, vector.body, middle.block
3817 //
3818 // middle.block:
3819 // x = v2(3)
3820 // br scalar.ph
3821 //
3822 // scalar.ph:
3823 // s_init = phi [x, middle.block], [a[-1], otherwise]
3824 // br scalar.body
3825 //
3826 // After execution completes the vector loop, we extract the next value of
3827 // the recurrence (x) to use as the initial value in the scalar loop.
3828
3829 // Extract the last vector element in the middle block. This will be the
3830 // initial value for the recurrence when jumping to the scalar loop.
3831 VPValue *PreviousDef = PhiR->getBackedgeValue();
3832 Value *Incoming = State.get(PreviousDef, UF - 1);
3833 auto *ExtractForScalar = Incoming;
3834 auto *IdxTy = Builder.getInt32Ty();
3835 if (VF.isVector()) {
3836 auto *One = ConstantInt::get(IdxTy, 1);
3837 Builder.SetInsertPoint(LoopMiddleBlock->getTerminator());
3838 auto *RuntimeVF = getRuntimeVF(Builder, IdxTy, VF);
3839 auto *LastIdx = Builder.CreateSub(RuntimeVF, One);
3840 ExtractForScalar = Builder.CreateExtractElement(ExtractForScalar, LastIdx,
3841 "vector.recur.extract");
3842 }
3843 // Extract the second last element in the middle block if the
3844 // Phi is used outside the loop. We need to extract the phi itself
3845 // and not the last element (the phi update in the current iteration). This
3846 // will be the value when jumping to the exit block from the LoopMiddleBlock,
3847 // when the scalar loop is not run at all.
3848 Value *ExtractForPhiUsedOutsideLoop = nullptr;
3849 if (VF.isVector()) {
3850 auto *RuntimeVF = getRuntimeVF(Builder, IdxTy, VF);
3851 auto *Idx = Builder.CreateSub(RuntimeVF, ConstantInt::get(IdxTy, 2));
3852 ExtractForPhiUsedOutsideLoop = Builder.CreateExtractElement(
3853 Incoming, Idx, "vector.recur.extract.for.phi");
3854 } else if (UF > 1)
3855 // When loop is unrolled without vectorizing, initialize
3856 // ExtractForPhiUsedOutsideLoop with the value just prior to unrolled value
3857 // of `Incoming`. This is analogous to the vectorized case above: extracting
3858 // the second last element when VF > 1.
3859 ExtractForPhiUsedOutsideLoop = State.get(PreviousDef, UF - 2);
3860
3861 // Fix the initial value of the original recurrence in the scalar loop.
3862 Builder.SetInsertPoint(&*LoopScalarPreHeader->begin());
3863 PHINode *Phi = cast<PHINode>(PhiR->getUnderlyingValue());
3864 auto *Start = Builder.CreatePHI(Phi->getType(), 2, "scalar.recur.init");
3865 auto *ScalarInit = PhiR->getStartValue()->getLiveInIRValue();
3866 for (auto *BB : predecessors(LoopScalarPreHeader)) {
3867 auto *Incoming = BB == LoopMiddleBlock ? ExtractForScalar : ScalarInit;
3868 Start->addIncoming(Incoming, BB);
3869 }
3870
3871 Phi->setIncomingValueForBlock(LoopScalarPreHeader, Start);
3872 Phi->setName("scalar.recur");
3873
3874 // Finally, fix users of the recurrence outside the loop. The users will need
3875 // either the last value of the scalar recurrence or the last value of the
3876 // vector recurrence we extracted in the middle block. Since the loop is in
3877 // LCSSA form, we just need to find all the phi nodes for the original scalar
3878 // recurrence in the exit block, and then add an edge for the middle block.
3879 // Note that LCSSA does not imply single entry when the original scalar loop
3880 // had multiple exiting edges (as we always run the last iteration in the
3881 // scalar epilogue); in that case, there is no edge from middle to exit and
3882 // and thus no phis which needed updated.
3883 if (!Cost->requiresScalarEpilogue(VF))
3884 for (PHINode &LCSSAPhi : LoopExitBlock->phis())
3885 if (llvm::is_contained(LCSSAPhi.incoming_values(), Phi))
3886 LCSSAPhi.addIncoming(ExtractForPhiUsedOutsideLoop, LoopMiddleBlock);
3887}
3888
3889void InnerLoopVectorizer::fixReduction(VPReductionPHIRecipe *PhiR,
3890 VPTransformState &State) {
3891 PHINode *OrigPhi = cast<PHINode>(PhiR->getUnderlyingValue());
3892 // Get it's reduction variable descriptor.
3893 assert(Legal->isReductionVariable(OrigPhi) &&(static_cast <bool> (Legal->isReductionVariable(OrigPhi
) && "Unable to find the reduction variable") ? void (
0) : __assert_fail ("Legal->isReductionVariable(OrigPhi) && \"Unable to find the reduction variable\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3894, __extension__
__PRETTY_FUNCTION__))
3894 "Unable to find the reduction variable")(static_cast <bool> (Legal->isReductionVariable(OrigPhi
) && "Unable to find the reduction variable") ? void (
0) : __assert_fail ("Legal->isReductionVariable(OrigPhi) && \"Unable to find the reduction variable\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3894, __extension__
__PRETTY_FUNCTION__))
;
3895 const RecurrenceDescriptor &RdxDesc = PhiR->getRecurrenceDescriptor();
3896
3897 RecurKind RK = RdxDesc.getRecurrenceKind();
3898 TrackingVH<Value> ReductionStartValue = RdxDesc.getRecurrenceStartValue();
3899 Instruction *LoopExitInst = RdxDesc.getLoopExitInstr();
3900 setDebugLocFromInst(ReductionStartValue);
3901
3902 VPValue *LoopExitInstDef = PhiR->getBackedgeValue();
3903 // This is the vector-clone of the value that leaves the loop.
3904 Type *VecTy = State.get(LoopExitInstDef, 0)->getType();
3905
3906 // Wrap flags are in general invalid after vectorization, clear them.
3907 clearReductionWrapFlags(RdxDesc, State);
3908
3909 // Before each round, move the insertion point right between
3910 // the PHIs and the values we are going to write.
3911 // This allows us to write both PHINodes and the extractelement
3912 // instructions.
3913 Builder.SetInsertPoint(&*LoopMiddleBlock->getFirstInsertionPt());
3914
3915 setDebugLocFromInst(LoopExitInst);
3916
3917 Type *PhiTy = OrigPhi->getType();
3918 BasicBlock *VectorLoopLatch =
3919 LI->getLoopFor(State.CFG.PrevBB)->getLoopLatch();
3920 // If tail is folded by masking, the vector value to leave the loop should be
3921 // a Select choosing between the vectorized LoopExitInst and vectorized Phi,
3922 // instead of the former. For an inloop reduction the reduction will already
3923 // be predicated, and does not need to be handled here.
3924 if (Cost->foldTailByMasking() && !PhiR->isInLoop()) {
3925 for (unsigned Part = 0; Part < UF; ++Part) {
3926 Value *VecLoopExitInst = State.get(LoopExitInstDef, Part);
3927 Value *Sel = nullptr;
3928 for (User *U : VecLoopExitInst->users()) {
3929 if (isa<SelectInst>(U)) {
3930 assert(!Sel && "Reduction exit feeding two selects")(static_cast <bool> (!Sel && "Reduction exit feeding two selects"
) ? void (0) : __assert_fail ("!Sel && \"Reduction exit feeding two selects\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3930, __extension__
__PRETTY_FUNCTION__))
;
3931 Sel = U;
3932 } else
3933 assert(isa<PHINode>(U) && "Reduction exit must feed Phi's or select")(static_cast <bool> (isa<PHINode>(U) && "Reduction exit must feed Phi's or select"
) ? void (0) : __assert_fail ("isa<PHINode>(U) && \"Reduction exit must feed Phi's or select\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3933, __extension__
__PRETTY_FUNCTION__))
;
3934 }
3935 assert(Sel && "Reduction exit feeds no select")(static_cast <bool> (Sel && "Reduction exit feeds no select"
) ? void (0) : __assert_fail ("Sel && \"Reduction exit feeds no select\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3935, __extension__
__PRETTY_FUNCTION__))
;
3936 State.reset(LoopExitInstDef, Sel, Part);
3937
3938 // If the target can create a predicated operator for the reduction at no
3939 // extra cost in the loop (for example a predicated vadd), it can be
3940 // cheaper for the select to remain in the loop than be sunk out of it,
3941 // and so use the select value for the phi instead of the old
3942 // LoopExitValue.
3943 if (PreferPredicatedReductionSelect ||
3944 TTI->preferPredicatedReductionSelect(
3945 RdxDesc.getOpcode(), PhiTy,
3946 TargetTransformInfo::ReductionFlags())) {
3947 auto *VecRdxPhi =
3948 cast<PHINode>(State.get(PhiR, Part));
3949 VecRdxPhi->setIncomingValueForBlock(VectorLoopLatch, Sel);
3950 }
3951 }
3952 }
3953
3954 // If the vector reduction can be performed in a smaller type, we truncate
3955 // then extend the loop exit value to enable InstCombine to evaluate the
3956 // entire expression in the smaller type.
3957 if (VF.isVector() && PhiTy != RdxDesc.getRecurrenceType()) {
3958 assert(!PhiR->isInLoop() && "Unexpected truncated inloop reduction!")(static_cast <bool> (!PhiR->isInLoop() && "Unexpected truncated inloop reduction!"
) ? void (0) : __assert_fail ("!PhiR->isInLoop() && \"Unexpected truncated inloop reduction!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 3958, __extension__
__PRETTY_FUNCTION__))
;
3959 Type *RdxVecTy = VectorType::get(RdxDesc.getRecurrenceType(), VF);
3960 Builder.SetInsertPoint(VectorLoopLatch->getTerminator());
3961 VectorParts RdxParts(UF);
3962 for (unsigned Part = 0; Part < UF; ++Part) {
3963 RdxParts[Part] = State.get(LoopExitInstDef, Part);
3964 Value *Trunc = Builder.CreateTrunc(RdxParts[Part], RdxVecTy);
3965 Value *Extnd = RdxDesc.isSigned() ? Builder.CreateSExt(Trunc, VecTy)
3966 : Builder.CreateZExt(Trunc, VecTy);
3967 for (User *U : llvm::make_early_inc_range(RdxParts[Part]->users()))
3968 if (U != Trunc) {
3969 U->replaceUsesOfWith(RdxParts[Part], Extnd);
3970 RdxParts[Part] = Extnd;
3971 }
3972 }
3973 Builder.SetInsertPoint(&*LoopMiddleBlock->getFirstInsertionPt());
3974 for (unsigned Part = 0; Part < UF; ++Part) {
3975 RdxParts[Part] = Builder.CreateTrunc(RdxParts[Part], RdxVecTy);
3976 State.reset(LoopExitInstDef, RdxParts[Part], Part);
3977 }
3978 }
3979
3980 // Reduce all of the unrolled parts into a single vector.
3981 Value *ReducedPartRdx = State.get(LoopExitInstDef, 0);
3982 unsigned Op = RecurrenceDescriptor::getOpcode(RK);
3983
3984 // The middle block terminator has already been assigned a DebugLoc here (the
3985 // OrigLoop's single latch terminator). We want the whole middle block to
3986 // appear to execute on this line because: (a) it is all compiler generated,
3987 // (b) these instructions are always executed after evaluating the latch
3988 // conditional branch, and (c) other passes may add new predecessors which
3989 // terminate on this line. This is the easiest way to ensure we don't
3990 // accidentally cause an extra step back into the loop while debugging.
3991 setDebugLocFromInst(LoopMiddleBlock->getTerminator());
3992 if (PhiR->isOrdered())
3993 ReducedPartRdx = State.get(LoopExitInstDef, UF - 1);
3994 else {
3995 // Floating-point operations should have some FMF to enable the reduction.
3996 IRBuilderBase::FastMathFlagGuard FMFG(Builder);
3997 Builder.setFastMathFlags(RdxDesc.getFastMathFlags());
3998 for (unsigned Part = 1; Part < UF; ++Part) {
3999 Value *RdxPart = State.get(LoopExitInstDef, Part);
4000 if (Op != Instruction::ICmp && Op != Instruction::FCmp) {
4001 ReducedPartRdx = Builder.CreateBinOp(
4002 (Instruction::BinaryOps)Op, RdxPart, ReducedPartRdx, "bin.rdx");
4003 } else if (RecurrenceDescriptor::isSelectCmpRecurrenceKind(RK))
4004 ReducedPartRdx = createSelectCmpOp(Builder, ReductionStartValue, RK,
4005 ReducedPartRdx, RdxPart);
4006 else
4007 ReducedPartRdx = createMinMaxOp(Builder, RK, ReducedPartRdx, RdxPart);
4008 }
4009 }
4010
4011 // Create the reduction after the loop. Note that inloop reductions create the
4012 // target reduction in the loop using a Reduction recipe.
4013 if (VF.isVector() && !PhiR->isInLoop()) {
4014 ReducedPartRdx =
4015 createTargetReduction(Builder, TTI, RdxDesc, ReducedPartRdx, OrigPhi);
4016 // If the reduction can be performed in a smaller type, we need to extend
4017 // the reduction to the wider type before we branch to the original loop.
4018 if (PhiTy != RdxDesc.getRecurrenceType())
4019 ReducedPartRdx = RdxDesc.isSigned()
4020 ? Builder.CreateSExt(ReducedPartRdx, PhiTy)
4021 : Builder.CreateZExt(ReducedPartRdx, PhiTy);
4022 }
4023
4024 PHINode *ResumePhi =
4025 dyn_cast<PHINode>(PhiR->getStartValue()->getUnderlyingValue());
4026
4027 // Create a phi node that merges control-flow from the backedge-taken check
4028 // block and the middle block.
4029 PHINode *BCBlockPhi = PHINode::Create(PhiTy, 2, "bc.merge.rdx",
4030 LoopScalarPreHeader->getTerminator());
4031
4032 // If we are fixing reductions in the epilogue loop then we should already
4033 // have created a bc.merge.rdx Phi after the main vector body. Ensure that
4034 // we carry over the incoming values correctly.
4035 for (auto *Incoming : predecessors(LoopScalarPreHeader)) {
4036 if (Incoming == LoopMiddleBlock)
4037 BCBlockPhi->addIncoming(ReducedPartRdx, Incoming);
4038 else if (ResumePhi && llvm::is_contained(ResumePhi->blocks(), Incoming))
4039 BCBlockPhi->addIncoming(ResumePhi->getIncomingValueForBlock(Incoming),
4040 Incoming);
4041 else
4042 BCBlockPhi->addIncoming(ReductionStartValue, Incoming);
4043 }
4044
4045 // Set the resume value for this reduction
4046 ReductionResumeValues.insert({&RdxDesc, BCBlockPhi});
4047
4048 // Now, we need to fix the users of the reduction variable
4049 // inside and outside of the scalar remainder loop.
4050
4051 // We know that the loop is in LCSSA form. We need to update the PHI nodes
4052 // in the exit blocks. See comment on analogous loop in
4053 // fixFirstOrderRecurrence for a more complete explaination of the logic.
4054 if (!Cost->requiresScalarEpilogue(VF))
4055 for (PHINode &LCSSAPhi : LoopExitBlock->phis())
4056 if (llvm::is_contained(LCSSAPhi.incoming_values(), LoopExitInst))
4057 LCSSAPhi.addIncoming(ReducedPartRdx, LoopMiddleBlock);
4058
4059 // Fix the scalar loop reduction variable with the incoming reduction sum
4060 // from the vector body and from the backedge value.
4061 int IncomingEdgeBlockIdx =
4062 OrigPhi->getBasicBlockIndex(OrigLoop->getLoopLatch());
4063 assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index")(static_cast <bool> (IncomingEdgeBlockIdx >= 0 &&
"Invalid block index") ? void (0) : __assert_fail ("IncomingEdgeBlockIdx >= 0 && \"Invalid block index\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4063, __extension__
__PRETTY_FUNCTION__))
;
4064 // Pick the other block.
4065 int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1);
4066 OrigPhi->setIncomingValue(SelfEdgeBlockIdx, BCBlockPhi);
4067 OrigPhi->setIncomingValue(IncomingEdgeBlockIdx, LoopExitInst);
4068}
4069
4070void InnerLoopVectorizer::clearReductionWrapFlags(const RecurrenceDescriptor &RdxDesc,
4071 VPTransformState &State) {
4072 RecurKind RK = RdxDesc.getRecurrenceKind();
4073 if (RK != RecurKind::Add && RK != RecurKind::Mul)
4074 return;
4075
4076 Instruction *LoopExitInstr = RdxDesc.getLoopExitInstr();
4077 assert(LoopExitInstr && "null loop exit instruction")(static_cast <bool> (LoopExitInstr && "null loop exit instruction"
) ? void (0) : __assert_fail ("LoopExitInstr && \"null loop exit instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4077, __extension__
__PRETTY_FUNCTION__))
;
4078 SmallVector<Instruction *, 8> Worklist;
4079 SmallPtrSet<Instruction *, 8> Visited;
4080 Worklist.push_back(LoopExitInstr);
4081 Visited.insert(LoopExitInstr);
4082
4083 while (!Worklist.empty()) {
4084 Instruction *Cur = Worklist.pop_back_val();
4085 if (isa<OverflowingBinaryOperator>(Cur))
4086 for (unsigned Part = 0; Part < UF; ++Part) {
4087 // FIXME: Should not rely on getVPValue at this point.
4088 Value *V = State.get(State.Plan->getVPValue(Cur, true), Part);
4089 cast<Instruction>(V)->dropPoisonGeneratingFlags();
4090 }
4091
4092 for (User *U : Cur->users()) {
4093 Instruction *UI = cast<Instruction>(U);
4094 if ((Cur != LoopExitInstr || OrigLoop->contains(UI->getParent())) &&
4095 Visited.insert(UI).second)
4096 Worklist.push_back(UI);
4097 }
4098 }
4099}
4100
4101void InnerLoopVectorizer::fixLCSSAPHIs(VPTransformState &State) {
4102 for (PHINode &LCSSAPhi : LoopExitBlock->phis()) {
4103 if (LCSSAPhi.getBasicBlockIndex(LoopMiddleBlock) != -1)
4104 // Some phis were already hand updated by the reduction and recurrence
4105 // code above, leave them alone.
4106 continue;
4107
4108 auto *IncomingValue = LCSSAPhi.getIncomingValue(0);
4109 // Non-instruction incoming values will have only one value.
4110
4111 VPLane Lane = VPLane::getFirstLane();
4112 if (isa<Instruction>(IncomingValue) &&
4113 !Cost->isUniformAfterVectorization(cast<Instruction>(IncomingValue),
4114 VF))
4115 Lane = VPLane::getLastLaneForVF(VF);
4116
4117 // Can be a loop invariant incoming value or the last scalar value to be
4118 // extracted from the vectorized loop.
4119 // FIXME: Should not rely on getVPValue at this point.
4120 Builder.SetInsertPoint(LoopMiddleBlock->getTerminator());
4121 Value *lastIncomingValue =
4122 OrigLoop->isLoopInvariant(IncomingValue)
4123 ? IncomingValue
4124 : State.get(State.Plan->getVPValue(IncomingValue, true),
4125 VPIteration(UF - 1, Lane));
4126 LCSSAPhi.addIncoming(lastIncomingValue, LoopMiddleBlock);
4127 }
4128}
4129
4130void InnerLoopVectorizer::sinkScalarOperands(Instruction *PredInst) {
4131 // The basic block and loop containing the predicated instruction.
4132 auto *PredBB = PredInst->getParent();
4133 auto *VectorLoop = LI->getLoopFor(PredBB);
4134
4135 // Initialize a worklist with the operands of the predicated instruction.
4136 SetVector<Value *> Worklist(PredInst->op_begin(), PredInst->op_end());
4137
4138 // Holds instructions that we need to analyze again. An instruction may be
4139 // reanalyzed if we don't yet know if we can sink it or not.
4140 SmallVector<Instruction *, 8> InstsToReanalyze;
4141
4142 // Returns true if a given use occurs in the predicated block. Phi nodes use
4143 // their operands in their corresponding predecessor blocks.
4144 auto isBlockOfUsePredicated = [&](Use &U) -> bool {
4145 auto *I = cast<Instruction>(U.getUser());
4146 BasicBlock *BB = I->getParent();
4147 if (auto *Phi = dyn_cast<PHINode>(I))
4148 BB = Phi->getIncomingBlock(
4149 PHINode::getIncomingValueNumForOperand(U.getOperandNo()));
4150 return BB == PredBB;
4151 };
4152
4153 // Iteratively sink the scalarized operands of the predicated instruction
4154 // into the block we created for it. When an instruction is sunk, it's
4155 // operands are then added to the worklist. The algorithm ends after one pass
4156 // through the worklist doesn't sink a single instruction.
4157 bool Changed;
4158 do {
4159 // Add the instructions that need to be reanalyzed to the worklist, and
4160 // reset the changed indicator.
4161 Worklist.insert(InstsToReanalyze.begin(), InstsToReanalyze.end());
4162 InstsToReanalyze.clear();
4163 Changed = false;
4164
4165 while (!Worklist.empty()) {
4166 auto *I = dyn_cast<Instruction>(Worklist.pop_back_val());
4167
4168 // We can't sink an instruction if it is a phi node, is not in the loop,
4169 // or may have side effects.
4170 if (!I || isa<PHINode>(I) || !VectorLoop->contains(I) ||
4171 I->mayHaveSideEffects())
4172 continue;
4173
4174 // If the instruction is already in PredBB, check if we can sink its
4175 // operands. In that case, VPlan's sinkScalarOperands() succeeded in
4176 // sinking the scalar instruction I, hence it appears in PredBB; but it
4177 // may have failed to sink I's operands (recursively), which we try
4178 // (again) here.
4179 if (I->getParent() == PredBB) {
4180 Worklist.insert(I->op_begin(), I->op_end());
4181 continue;
4182 }
4183
4184 // It's legal to sink the instruction if all its uses occur in the
4185 // predicated block. Otherwise, there's nothing to do yet, and we may
4186 // need to reanalyze the instruction.
4187 if (!llvm::all_of(I->uses(), isBlockOfUsePredicated)) {
4188 InstsToReanalyze.push_back(I);
4189 continue;
4190 }
4191
4192 // Move the instruction to the beginning of the predicated block, and add
4193 // it's operands to the worklist.
4194 I->moveBefore(&*PredBB->getFirstInsertionPt());
4195 Worklist.insert(I->op_begin(), I->op_end());
4196
4197 // The sinking may have enabled other instructions to be sunk, so we will
4198 // need to iterate.
4199 Changed = true;
4200 }
4201 } while (Changed);
4202}
4203
4204void InnerLoopVectorizer::fixNonInductionPHIs(VPTransformState &State) {
4205 for (PHINode *OrigPhi : OrigPHIsToFix) {
4206 VPWidenPHIRecipe *VPPhi =
4207 cast<VPWidenPHIRecipe>(State.Plan->getVPValue(OrigPhi));
4208 PHINode *NewPhi = cast<PHINode>(State.get(VPPhi, 0));
4209 // Make sure the builder has a valid insert point.
4210 Builder.SetInsertPoint(NewPhi);
4211 for (unsigned i = 0; i < VPPhi->getNumOperands(); ++i) {
4212 VPValue *Inc = VPPhi->getIncomingValue(i);
4213 VPBasicBlock *VPBB = VPPhi->getIncomingBlock(i);
4214 NewPhi->addIncoming(State.get(Inc, 0), State.CFG.VPBB2IRBB[VPBB]);
4215 }
4216 }
4217}
4218
4219bool InnerLoopVectorizer::useOrderedReductions(
4220 const RecurrenceDescriptor &RdxDesc) {
4221 return Cost->useOrderedReductions(RdxDesc);
4222}
4223
4224void InnerLoopVectorizer::widenPHIInstruction(Instruction *PN,
4225 VPWidenPHIRecipe *PhiR,
4226 VPTransformState &State) {
4227 PHINode *P = cast<PHINode>(PN);
4228 if (EnableVPlanNativePath) {
4229 // Currently we enter here in the VPlan-native path for non-induction
4230 // PHIs where all control flow is uniform. We simply widen these PHIs.
4231 // Create a vector phi with no operands - the vector phi operands will be
4232 // set at the end of vector code generation.
4233 Type *VecTy = (State.VF.isScalar())
4234 ? PN->getType()
4235 : VectorType::get(PN->getType(), State.VF);
4236 Value *VecPhi = Builder.CreatePHI(VecTy, PN->getNumOperands(), "vec.phi");
4237 State.set(PhiR, VecPhi, 0);
4238 OrigPHIsToFix.push_back(P);
4239
4240 return;
4241 }
4242
4243 assert(PN->getParent() == OrigLoop->getHeader() &&(static_cast <bool> (PN->getParent() == OrigLoop->
getHeader() && "Non-header phis should have been handled elsewhere"
) ? void (0) : __assert_fail ("PN->getParent() == OrigLoop->getHeader() && \"Non-header phis should have been handled elsewhere\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4244, __extension__
__PRETTY_FUNCTION__))
4244 "Non-header phis should have been handled elsewhere")(static_cast <bool> (PN->getParent() == OrigLoop->
getHeader() && "Non-header phis should have been handled elsewhere"
) ? void (0) : __assert_fail ("PN->getParent() == OrigLoop->getHeader() && \"Non-header phis should have been handled elsewhere\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4244, __extension__
__PRETTY_FUNCTION__))
;
4245
4246 // In order to support recurrences we need to be able to vectorize Phi nodes.
4247 // Phi nodes have cycles, so we need to vectorize them in two stages. This is
4248 // stage #1: We create a new vector PHI node with no incoming edges. We'll use
4249 // this value when we vectorize all of the instructions that use the PHI.
4250
4251 assert(!Legal->isReductionVariable(P) &&(static_cast <bool> (!Legal->isReductionVariable(P) &&
"reductions should be handled elsewhere") ? void (0) : __assert_fail
("!Legal->isReductionVariable(P) && \"reductions should be handled elsewhere\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4252, __extension__
__PRETTY_FUNCTION__))
4252 "reductions should be handled elsewhere")(static_cast <bool> (!Legal->isReductionVariable(P) &&
"reductions should be handled elsewhere") ? void (0) : __assert_fail
("!Legal->isReductionVariable(P) && \"reductions should be handled elsewhere\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4252, __extension__
__PRETTY_FUNCTION__))
;
4253
4254 setDebugLocFromInst(P);
4255
4256 // This PHINode must be an induction variable.
4257 // Make sure that we know about it.
4258 assert(Legal->getInductionVars().count(P) && "Not an induction variable")(static_cast <bool> (Legal->getInductionVars().count
(P) && "Not an induction variable") ? void (0) : __assert_fail
("Legal->getInductionVars().count(P) && \"Not an induction variable\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4258, __extension__
__PRETTY_FUNCTION__))
;
4259
4260 InductionDescriptor II = Legal->getInductionVars().lookup(P);
4261 const DataLayout &DL = OrigLoop->getHeader()->getModule()->getDataLayout();
4262
4263 auto *IVR = PhiR->getParent()->getPlan()->getCanonicalIV();
4264 PHINode *CanonicalIV = cast<PHINode>(State.get(IVR, 0));
4265
4266 // FIXME: The newly created binary instructions should contain nsw/nuw flags,
4267 // which can be found from the original scalar operations.
4268 switch (II.getKind()) {
4269 case InductionDescriptor::IK_NoInduction:
4270 llvm_unreachable("Unknown induction")::llvm::llvm_unreachable_internal("Unknown induction", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 4270)
;
4271 case InductionDescriptor::IK_IntInduction:
4272 case InductionDescriptor::IK_FpInduction:
4273 llvm_unreachable("Integer/fp induction is handled elsewhere.")::llvm::llvm_unreachable_internal("Integer/fp induction is handled elsewhere."
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4273)
;
4274 case InductionDescriptor::IK_PtrInduction: {
4275 // Handle the pointer induction variable case.
4276 assert(P->getType()->isPointerTy() && "Unexpected type.")(static_cast <bool> (P->getType()->isPointerTy() &&
"Unexpected type.") ? void (0) : __assert_fail ("P->getType()->isPointerTy() && \"Unexpected type.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4276, __extension__
__PRETTY_FUNCTION__))
;
4277
4278 if (all_of(PhiR->users(), [PhiR](const VPUser *U) {
4279 return cast<VPRecipeBase>(U)->usesScalars(PhiR);
4280 })) {
4281 // This is the normalized GEP that starts counting at zero.
4282 Value *PtrInd =
4283 Builder.CreateSExtOrTrunc(CanonicalIV, II.getStep()->getType());
4284 // Determine the number of scalars we need to generate for each unroll
4285 // iteration. If the instruction is uniform, we only need to generate the
4286 // first lane. Otherwise, we generate all VF values.
4287 bool IsUniform = vputils::onlyFirstLaneUsed(PhiR);
4288 assert((IsUniform || !State.VF.isScalable()) &&(static_cast <bool> ((IsUniform || !State.VF.isScalable
()) && "Cannot scalarize a scalable VF") ? void (0) :
__assert_fail ("(IsUniform || !State.VF.isScalable()) && \"Cannot scalarize a scalable VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4289, __extension__
__PRETTY_FUNCTION__))
4289 "Cannot scalarize a scalable VF")(static_cast <bool> ((IsUniform || !State.VF.isScalable
()) && "Cannot scalarize a scalable VF") ? void (0) :
__assert_fail ("(IsUniform || !State.VF.isScalable()) && \"Cannot scalarize a scalable VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4289, __extension__
__PRETTY_FUNCTION__))
;
4290 unsigned Lanes = IsUniform ? 1 : State.VF.getFixedValue();
4291
4292 for (unsigned Part = 0; Part < UF; ++Part) {
4293 Value *PartStart =
4294 createStepForVF(Builder, PtrInd->getType(), VF, Part);
4295
4296 for (unsigned Lane = 0; Lane < Lanes; ++Lane) {
4297 Value *Idx = Builder.CreateAdd(
4298 PartStart, ConstantInt::get(PtrInd->getType(), Lane));
4299 Value *GlobalIdx = Builder.CreateAdd(PtrInd, Idx);
4300
4301 Value *Step = CreateStepValue(II.getStep(), *PSE.getSE(),
4302 State.CFG.PrevBB->getTerminator());
4303 Value *SclrGep = emitTransformedIndex(Builder, GlobalIdx,
4304 II.getStartValue(), Step, II);
4305 SclrGep->setName("next.gep");
4306 State.set(PhiR, SclrGep, VPIteration(Part, Lane));
4307 }
4308 }
4309 return;
4310 }
4311 assert(isa<SCEVConstant>(II.getStep()) &&(static_cast <bool> (isa<SCEVConstant>(II.getStep
()) && "Induction step not a SCEV constant!") ? void (
0) : __assert_fail ("isa<SCEVConstant>(II.getStep()) && \"Induction step not a SCEV constant!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4312, __extension__
__PRETTY_FUNCTION__))
4312 "Induction step not a SCEV constant!")(static_cast <bool> (isa<SCEVConstant>(II.getStep
()) && "Induction step not a SCEV constant!") ? void (
0) : __assert_fail ("isa<SCEVConstant>(II.getStep()) && \"Induction step not a SCEV constant!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4312, __extension__
__PRETTY_FUNCTION__))
;
4313 Type *PhiType = II.getStep()->getType();
4314
4315 // Build a pointer phi
4316 Value *ScalarStartValue = PhiR->getStartValue()->getLiveInIRValue();
4317 Type *ScStValueType = ScalarStartValue->getType();
4318 PHINode *NewPointerPhi =
4319 PHINode::Create(ScStValueType, 2, "pointer.phi", CanonicalIV);
4320 NewPointerPhi->addIncoming(ScalarStartValue, LoopVectorPreHeader);
4321
4322 // A pointer induction, performed by using a gep
4323 BasicBlock *LoopLatch = LI->getLoopFor(State.CFG.PrevBB)->getLoopLatch();
4324 Instruction *InductionLoc = LoopLatch->getTerminator();
4325 const SCEV *ScalarStep = II.getStep();
4326 SCEVExpander Exp(*PSE.getSE(), DL, "induction");
4327 Value *ScalarStepValue =
4328 Exp.expandCodeFor(ScalarStep, PhiType, InductionLoc);
4329 Value *RuntimeVF = getRuntimeVF(Builder, PhiType, VF);
4330 Value *NumUnrolledElems =
4331 Builder.CreateMul(RuntimeVF, ConstantInt::get(PhiType, State.UF));
4332 Value *InductionGEP = GetElementPtrInst::Create(
4333 II.getElementType(), NewPointerPhi,
4334 Builder.CreateMul(ScalarStepValue, NumUnrolledElems), "ptr.ind",
4335 InductionLoc);
4336 NewPointerPhi->addIncoming(InductionGEP, LoopLatch);
4337
4338 // Create UF many actual address geps that use the pointer
4339 // phi as base and a vectorized version of the step value
4340 // (<step*0, ..., step*N>) as offset.
4341 for (unsigned Part = 0; Part < State.UF; ++Part) {
4342 Type *VecPhiType = VectorType::get(PhiType, State.VF);
4343 Value *StartOffsetScalar =
4344 Builder.CreateMul(RuntimeVF, ConstantInt::get(PhiType, Part));
4345 Value *StartOffset =
4346 Builder.CreateVectorSplat(State.VF, StartOffsetScalar);
4347 // Create a vector of consecutive numbers from zero to VF.
4348 StartOffset =
4349 Builder.CreateAdd(StartOffset, Builder.CreateStepVector(VecPhiType));
4350
4351 Value *GEP = Builder.CreateGEP(
4352 II.getElementType(), NewPointerPhi,
4353 Builder.CreateMul(
4354 StartOffset, Builder.CreateVectorSplat(State.VF, ScalarStepValue),
4355 "vector.gep"));
4356 State.set(PhiR, GEP, Part);
4357 }
4358 }
4359 }
4360}
4361
4362/// A helper function for checking whether an integer division-related
4363/// instruction may divide by zero (in which case it must be predicated if
4364/// executed conditionally in the scalar code).
4365/// TODO: It may be worthwhile to generalize and check isKnownNonZero().
4366/// Non-zero divisors that are non compile-time constants will not be
4367/// converted into multiplication, so we will still end up scalarizing
4368/// the division, but can do so w/o predication.
4369static bool mayDivideByZero(Instruction &I) {
4370 assert((I.getOpcode() == Instruction::UDiv ||(static_cast <bool> ((I.getOpcode() == Instruction::UDiv
|| I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction
::URem || I.getOpcode() == Instruction::SRem) && "Unexpected instruction"
) ? void (0) : __assert_fail ("(I.getOpcode() == Instruction::UDiv || I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction::URem || I.getOpcode() == Instruction::SRem) && \"Unexpected instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4374, __extension__
__PRETTY_FUNCTION__))
4371 I.getOpcode() == Instruction::SDiv ||(static_cast <bool> ((I.getOpcode() == Instruction::UDiv
|| I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction
::URem || I.getOpcode() == Instruction::SRem) && "Unexpected instruction"
) ? void (0) : __assert_fail ("(I.getOpcode() == Instruction::UDiv || I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction::URem || I.getOpcode() == Instruction::SRem) && \"Unexpected instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4374, __extension__
__PRETTY_FUNCTION__))
4372 I.getOpcode() == Instruction::URem ||(static_cast <bool> ((I.getOpcode() == Instruction::UDiv
|| I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction
::URem || I.getOpcode() == Instruction::SRem) && "Unexpected instruction"
) ? void (0) : __assert_fail ("(I.getOpcode() == Instruction::UDiv || I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction::URem || I.getOpcode() == Instruction::SRem) && \"Unexpected instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4374, __extension__
__PRETTY_FUNCTION__))
4373 I.getOpcode() == Instruction::SRem) &&(static_cast <bool> ((I.getOpcode() == Instruction::UDiv
|| I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction
::URem || I.getOpcode() == Instruction::SRem) && "Unexpected instruction"
) ? void (0) : __assert_fail ("(I.getOpcode() == Instruction::UDiv || I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction::URem || I.getOpcode() == Instruction::SRem) && \"Unexpected instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4374, __extension__
__PRETTY_FUNCTION__))
4374 "Unexpected instruction")(static_cast <bool> ((I.getOpcode() == Instruction::UDiv
|| I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction
::URem || I.getOpcode() == Instruction::SRem) && "Unexpected instruction"
) ? void (0) : __assert_fail ("(I.getOpcode() == Instruction::UDiv || I.getOpcode() == Instruction::SDiv || I.getOpcode() == Instruction::URem || I.getOpcode() == Instruction::SRem) && \"Unexpected instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4374, __extension__
__PRETTY_FUNCTION__))
;
4375 Value *Divisor = I.getOperand(1);
4376 auto *CInt = dyn_cast<ConstantInt>(Divisor);
4377 return !CInt || CInt->isZero();
4378}
4379
4380void InnerLoopVectorizer::widenCallInstruction(CallInst &I, VPValue *Def,
4381 VPUser &ArgOperands,
4382 VPTransformState &State) {
4383 assert(!isa<DbgInfoIntrinsic>(I) &&(static_cast <bool> (!isa<DbgInfoIntrinsic>(I) &&
"DbgInfoIntrinsic should have been dropped during VPlan construction"
) ? void (0) : __assert_fail ("!isa<DbgInfoIntrinsic>(I) && \"DbgInfoIntrinsic should have been dropped during VPlan construction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4384, __extension__
__PRETTY_FUNCTION__))
4384 "DbgInfoIntrinsic should have been dropped during VPlan construction")(static_cast <bool> (!isa<DbgInfoIntrinsic>(I) &&
"DbgInfoIntrinsic should have been dropped during VPlan construction"
) ? void (0) : __assert_fail ("!isa<DbgInfoIntrinsic>(I) && \"DbgInfoIntrinsic should have been dropped during VPlan construction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4384, __extension__
__PRETTY_FUNCTION__))
;
4385 setDebugLocFromInst(&I);
4386
4387 Module *M = I.getParent()->getParent()->getParent();
4388 auto *CI = cast<CallInst>(&I);
4389
4390 SmallVector<Type *, 4> Tys;
4391 for (Value *ArgOperand : CI->args())
4392 Tys.push_back(ToVectorTy(ArgOperand->getType(), VF.getKnownMinValue()));
4393
4394 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
4395
4396 // The flag shows whether we use Intrinsic or a usual Call for vectorized
4397 // version of the instruction.
4398 // Is it beneficial to perform intrinsic call compared to lib call?
4399 bool NeedToScalarize = false;
4400 InstructionCost CallCost = Cost->getVectorCallCost(CI, VF, NeedToScalarize);
4401 InstructionCost IntrinsicCost = ID ? Cost->getVectorIntrinsicCost(CI, VF) : 0;
4402 bool UseVectorIntrinsic = ID && IntrinsicCost <= CallCost;
4403 assert((UseVectorIntrinsic || !NeedToScalarize) &&(static_cast <bool> ((UseVectorIntrinsic || !NeedToScalarize
) && "Instruction should be scalarized elsewhere.") ?
void (0) : __assert_fail ("(UseVectorIntrinsic || !NeedToScalarize) && \"Instruction should be scalarized elsewhere.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4404, __extension__
__PRETTY_FUNCTION__))
4404 "Instruction should be scalarized elsewhere.")(static_cast <bool> ((UseVectorIntrinsic || !NeedToScalarize
) && "Instruction should be scalarized elsewhere.") ?
void (0) : __assert_fail ("(UseVectorIntrinsic || !NeedToScalarize) && \"Instruction should be scalarized elsewhere.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4404, __extension__
__PRETTY_FUNCTION__))
;
4405 assert((IntrinsicCost.isValid() || CallCost.isValid()) &&(static_cast <bool> ((IntrinsicCost.isValid() || CallCost
.isValid()) && "Either the intrinsic cost or vector call cost must be valid"
) ? void (0) : __assert_fail ("(IntrinsicCost.isValid() || CallCost.isValid()) && \"Either the intrinsic cost or vector call cost must be valid\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4406, __extension__
__PRETTY_FUNCTION__))
4406 "Either the intrinsic cost or vector call cost must be valid")(static_cast <bool> ((IntrinsicCost.isValid() || CallCost
.isValid()) && "Either the intrinsic cost or vector call cost must be valid"
) ? void (0) : __assert_fail ("(IntrinsicCost.isValid() || CallCost.isValid()) && \"Either the intrinsic cost or vector call cost must be valid\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4406, __extension__
__PRETTY_FUNCTION__))
;
4407
4408 for (unsigned Part = 0; Part < UF; ++Part) {
4409 SmallVector<Type *, 2> TysForDecl = {CI->getType()};
4410 SmallVector<Value *, 4> Args;
4411 for (auto &I : enumerate(ArgOperands.operands())) {
4412 // Some intrinsics have a scalar argument - don't replace it with a
4413 // vector.
4414 Value *Arg;
4415 if (!UseVectorIntrinsic || !hasVectorInstrinsicScalarOpd(ID, I.index()))
4416 Arg = State.get(I.value(), Part);
4417 else {
4418 Arg = State.get(I.value(), VPIteration(0, 0));
4419 if (hasVectorInstrinsicOverloadedScalarOpd(ID, I.index()))
4420 TysForDecl.push_back(Arg->getType());
4421 }
4422 Args.push_back(Arg);
4423 }
4424
4425 Function *VectorF;
4426 if (UseVectorIntrinsic) {
4427 // Use vector version of the intrinsic.
4428 if (VF.isVector())
4429 TysForDecl[0] = VectorType::get(CI->getType()->getScalarType(), VF);
4430 VectorF = Intrinsic::getDeclaration(M, ID, TysForDecl);
4431 assert(VectorF && "Can't retrieve vector intrinsic.")(static_cast <bool> (VectorF && "Can't retrieve vector intrinsic."
) ? void (0) : __assert_fail ("VectorF && \"Can't retrieve vector intrinsic.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4431, __extension__
__PRETTY_FUNCTION__))
;
4432 } else {
4433 // Use vector version of the function call.
4434 const VFShape Shape = VFShape::get(*CI, VF, false /*HasGlobalPred*/);
4435#ifndef NDEBUG
4436 assert(VFDatabase(*CI).getVectorizedFunction(Shape) != nullptr &&(static_cast <bool> (VFDatabase(*CI).getVectorizedFunction
(Shape) != nullptr && "Can't create vector function."
) ? void (0) : __assert_fail ("VFDatabase(*CI).getVectorizedFunction(Shape) != nullptr && \"Can't create vector function.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4437, __extension__
__PRETTY_FUNCTION__))
4437 "Can't create vector function.")(static_cast <bool> (VFDatabase(*CI).getVectorizedFunction
(Shape) != nullptr && "Can't create vector function."
) ? void (0) : __assert_fail ("VFDatabase(*CI).getVectorizedFunction(Shape) != nullptr && \"Can't create vector function.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4437, __extension__
__PRETTY_FUNCTION__))
;
4438#endif
4439 VectorF = VFDatabase(*CI).getVectorizedFunction(Shape);
4440 }
4441 SmallVector<OperandBundleDef, 1> OpBundles;
4442 CI->getOperandBundlesAsDefs(OpBundles);
4443 CallInst *V = Builder.CreateCall(VectorF, Args, OpBundles);
4444
4445 if (isa<FPMathOperator>(V))
4446 V->copyFastMathFlags(CI);
4447
4448 State.set(Def, V, Part);
4449 addMetadata(V, &I);
4450 }
4451}
4452
4453void LoopVectorizationCostModel::collectLoopScalars(ElementCount VF) {
4454 // We should not collect Scalars more than once per VF. Right now, this
4455 // function is called from collectUniformsAndScalars(), which already does
4456 // this check. Collecting Scalars for VF=1 does not make any sense.
4457 assert(VF.isVector() && Scalars.find(VF) == Scalars.end() &&(static_cast <bool> (VF.isVector() && Scalars.find
(VF) == Scalars.end() && "This function should not be visited twice for the same VF"
) ? void (0) : __assert_fail ("VF.isVector() && Scalars.find(VF) == Scalars.end() && \"This function should not be visited twice for the same VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4458, __extension__
__PRETTY_FUNCTION__))
4458 "This function should not be visited twice for the same VF")(static_cast <bool> (VF.isVector() && Scalars.find
(VF) == Scalars.end() && "This function should not be visited twice for the same VF"
) ? void (0) : __assert_fail ("VF.isVector() && Scalars.find(VF) == Scalars.end() && \"This function should not be visited twice for the same VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4458, __extension__
__PRETTY_FUNCTION__))
;
4459
4460 // This avoids any chances of creating a REPLICATE recipe during planning
4461 // since that would result in generation of scalarized code during execution,
4462 // which is not supported for scalable vectors.
4463 if (VF.isScalable()) {
4464 Scalars[VF].insert(Uniforms[VF].begin(), Uniforms[VF].end());
4465 return;
4466 }
4467
4468 SmallSetVector<Instruction *, 8> Worklist;
4469
4470 // These sets are used to seed the analysis with pointers used by memory
4471 // accesses that will remain scalar.
4472 SmallSetVector<Instruction *, 8> ScalarPtrs;
4473 SmallPtrSet<Instruction *, 8> PossibleNonScalarPtrs;
4474 auto *Latch = TheLoop->getLoopLatch();
4475
4476 // A helper that returns true if the use of Ptr by MemAccess will be scalar.
4477 // The pointer operands of loads and stores will be scalar as long as the
4478 // memory access is not a gather or scatter operation. The value operand of a
4479 // store will remain scalar if the store is scalarized.
4480 auto isScalarUse = [&](Instruction *MemAccess, Value *Ptr) {
4481 InstWidening WideningDecision = getWideningDecision(MemAccess, VF);
4482 assert(WideningDecision != CM_Unknown &&(static_cast <bool> (WideningDecision != CM_Unknown &&
"Widening decision should be ready at this moment") ? void (
0) : __assert_fail ("WideningDecision != CM_Unknown && \"Widening decision should be ready at this moment\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4483, __extension__
__PRETTY_FUNCTION__))
4483 "Widening decision should be ready at this moment")(static_cast <bool> (WideningDecision != CM_Unknown &&
"Widening decision should be ready at this moment") ? void (
0) : __assert_fail ("WideningDecision != CM_Unknown && \"Widening decision should be ready at this moment\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4483, __extension__
__PRETTY_FUNCTION__))
;
4484 if (auto *Store = dyn_cast<StoreInst>(MemAccess))
4485 if (Ptr == Store->getValueOperand())
4486 return WideningDecision == CM_Scalarize;
4487 assert(Ptr == getLoadStorePointerOperand(MemAccess) &&(static_cast <bool> (Ptr == getLoadStorePointerOperand(
MemAccess) && "Ptr is neither a value or pointer operand"
) ? void (0) : __assert_fail ("Ptr == getLoadStorePointerOperand(MemAccess) && \"Ptr is neither a value or pointer operand\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4488, __extension__
__PRETTY_FUNCTION__))
4488 "Ptr is neither a value or pointer operand")(static_cast <bool> (Ptr == getLoadStorePointerOperand(
MemAccess) && "Ptr is neither a value or pointer operand"
) ? void (0) : __assert_fail ("Ptr == getLoadStorePointerOperand(MemAccess) && \"Ptr is neither a value or pointer operand\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4488, __extension__
__PRETTY_FUNCTION__))
;
4489 return WideningDecision != CM_GatherScatter;
4490 };
4491
4492 // A helper that returns true if the given value is a bitcast or
4493 // getelementptr instruction contained in the loop.
4494 auto isLoopVaryingBitCastOrGEP = [&](Value *V) {
4495 return ((isa<BitCastInst>(V) && V->getType()->isPointerTy()) ||
4496 isa<GetElementPtrInst>(V)) &&
4497 !TheLoop->isLoopInvariant(V);
4498 };
4499
4500 // A helper that evaluates a memory access's use of a pointer. If the use will
4501 // be a scalar use and the pointer is only used by memory accesses, we place
4502 // the pointer in ScalarPtrs. Otherwise, the pointer is placed in
4503 // PossibleNonScalarPtrs.
4504 auto evaluatePtrUse = [&](Instruction *MemAccess, Value *Ptr) {
4505 // We only care about bitcast and getelementptr instructions contained in
4506 // the loop.
4507 if (!isLoopVaryingBitCastOrGEP(Ptr))
4508 return;
4509
4510 // If the pointer has already been identified as scalar (e.g., if it was
4511 // also identified as uniform), there's nothing to do.
4512 auto *I = cast<Instruction>(Ptr);
4513 if (Worklist.count(I))
4514 return;
4515
4516 // If the use of the pointer will be a scalar use, and all users of the
4517 // pointer are memory accesses, place the pointer in ScalarPtrs. Otherwise,
4518 // place the pointer in PossibleNonScalarPtrs.
4519 if (isScalarUse(MemAccess, Ptr) && llvm::all_of(I->users(), [&](User *U) {
4520 return isa<LoadInst>(U) || isa<StoreInst>(U);
4521 }))
4522 ScalarPtrs.insert(I);
4523 else
4524 PossibleNonScalarPtrs.insert(I);
4525 };
4526
4527 // We seed the scalars analysis with three classes of instructions: (1)
4528 // instructions marked uniform-after-vectorization and (2) bitcast,
4529 // getelementptr and (pointer) phi instructions used by memory accesses
4530 // requiring a scalar use.
4531 //
4532 // (1) Add to the worklist all instructions that have been identified as
4533 // uniform-after-vectorization.
4534 Worklist.insert(Uniforms[VF].begin(), Uniforms[VF].end());
4535
4536 // (2) Add to the worklist all bitcast and getelementptr instructions used by
4537 // memory accesses requiring a scalar use. The pointer operands of loads and
4538 // stores will be scalar as long as the memory accesses is not a gather or
4539 // scatter operation. The value operand of a store will remain scalar if the
4540 // store is scalarized.
4541 for (auto *BB : TheLoop->blocks())
4542 for (auto &I : *BB) {
4543 if (auto *Load = dyn_cast<LoadInst>(&I)) {
4544 evaluatePtrUse(Load, Load->getPointerOperand());
4545 } else if (auto *Store = dyn_cast<StoreInst>(&I)) {
4546 evaluatePtrUse(Store, Store->getPointerOperand());
4547 evaluatePtrUse(Store, Store->getValueOperand());
4548 }
4549 }
4550 for (auto *I : ScalarPtrs)
4551 if (!PossibleNonScalarPtrs.count(I)) {
4552 LLVM_DEBUG(dbgs() << "LV: Found scalar instruction: " << *I << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found scalar instruction: "
<< *I << "\n"; } } while (false)
;
4553 Worklist.insert(I);
4554 }
4555
4556 // Insert the forced scalars.
4557 // FIXME: Currently widenPHIInstruction() often creates a dead vector
4558 // induction variable when the PHI user is scalarized.
4559 auto ForcedScalar = ForcedScalars.find(VF);
4560 if (ForcedScalar != ForcedScalars.end())
4561 for (auto *I : ForcedScalar->second)
4562 Worklist.insert(I);
4563
4564 // Expand the worklist by looking through any bitcasts and getelementptr
4565 // instructions we've already identified as scalar. This is similar to the
4566 // expansion step in collectLoopUniforms(); however, here we're only
4567 // expanding to include additional bitcasts and getelementptr instructions.
4568 unsigned Idx = 0;
4569 while (Idx != Worklist.size()) {
4570 Instruction *Dst = Worklist[Idx++];
4571 if (!isLoopVaryingBitCastOrGEP(Dst->getOperand(0)))
4572 continue;
4573 auto *Src = cast<Instruction>(Dst->getOperand(0));
4574 if (llvm::all_of(Src->users(), [&](User *U) -> bool {
4575 auto *J = cast<Instruction>(U);
4576 return !TheLoop->contains(J) || Worklist.count(J) ||
4577 ((isa<LoadInst>(J) || isa<StoreInst>(J)) &&
4578 isScalarUse(J, Src));
4579 })) {
4580 Worklist.insert(Src);
4581 LLVM_DEBUG(dbgs() << "LV: Found scalar instruction: " << *Src << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found scalar instruction: "
<< *Src << "\n"; } } while (false)
;
4582 }
4583 }
4584
4585 // An induction variable will remain scalar if all users of the induction
4586 // variable and induction variable update remain scalar.
4587 for (auto &Induction : Legal->getInductionVars()) {
4588 auto *Ind = Induction.first;
4589 auto *IndUpdate = cast<Instruction>(Ind->getIncomingValueForBlock(Latch));
4590
4591 // If tail-folding is applied, the primary induction variable will be used
4592 // to feed a vector compare.
4593 if (Ind == Legal->getPrimaryInduction() && foldTailByMasking())
4594 continue;
4595
4596 // Returns true if \p Indvar is a pointer induction that is used directly by
4597 // load/store instruction \p I.
4598 auto IsDirectLoadStoreFromPtrIndvar = [&](Instruction *Indvar,
4599 Instruction *I) {
4600 return Induction.second.getKind() ==
4601 InductionDescriptor::IK_PtrInduction &&
4602 (isa<LoadInst>(I) || isa<StoreInst>(I)) &&
4603 Indvar == getLoadStorePointerOperand(I) && isScalarUse(I, Indvar);
4604 };
4605
4606 // Determine if all users of the induction variable are scalar after
4607 // vectorization.
4608 auto ScalarInd = llvm::all_of(Ind->users(), [&](User *U) -> bool {
4609 auto *I = cast<Instruction>(U);
4610 return I == IndUpdate || !TheLoop->contains(I) || Worklist.count(I) ||
4611 IsDirectLoadStoreFromPtrIndvar(Ind, I);
4612 });
4613 if (!ScalarInd)
4614 continue;
4615
4616 // Determine if all users of the induction variable update instruction are
4617 // scalar after vectorization.
4618 auto ScalarIndUpdate =
4619 llvm::all_of(IndUpdate->users(), [&](User *U) -> bool {
4620 auto *I = cast<Instruction>(U);
4621 return I == Ind || !TheLoop->contains(I) || Worklist.count(I) ||
4622 IsDirectLoadStoreFromPtrIndvar(IndUpdate, I);
4623 });
4624 if (!ScalarIndUpdate)
4625 continue;
4626
4627 // The induction variable and its update instruction will remain scalar.
4628 Worklist.insert(Ind);
4629 Worklist.insert(IndUpdate);
4630 LLVM_DEBUG(dbgs() << "LV: Found scalar instruction: " << *Ind << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found scalar instruction: "
<< *Ind << "\n"; } } while (false)
;
4631 LLVM_DEBUG(dbgs() << "LV: Found scalar instruction: " << *IndUpdatedo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found scalar instruction: "
<< *IndUpdate << "\n"; } } while (false)
4632 << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found scalar instruction: "
<< *IndUpdate << "\n"; } } while (false)
;
4633 }
4634
4635 Scalars[VF].insert(Worklist.begin(), Worklist.end());
4636}
4637
4638bool LoopVectorizationCostModel::isScalarWithPredication(
4639 Instruction *I, ElementCount VF) const {
4640 if (!blockNeedsPredicationForAnyReason(I->getParent()))
4641 return false;
4642 switch(I->getOpcode()) {
4643 default:
4644 break;
4645 case Instruction::Load:
4646 case Instruction::Store: {
4647 if (!Legal->isMaskRequired(I))
4648 return false;
4649 auto *Ptr = getLoadStorePointerOperand(I);
4650 auto *Ty = getLoadStoreType(I);
4651 Type *VTy = Ty;
4652 if (VF.isVector())
4653 VTy = VectorType::get(Ty, VF);
4654 const Align Alignment = getLoadStoreAlignment(I);
4655 return isa<LoadInst>(I) ? !(isLegalMaskedLoad(Ty, Ptr, Alignment) ||
4656 TTI.isLegalMaskedGather(VTy, Alignment))
4657 : !(isLegalMaskedStore(Ty, Ptr, Alignment) ||
4658 TTI.isLegalMaskedScatter(VTy, Alignment));
4659 }
4660 case Instruction::UDiv:
4661 case Instruction::SDiv:
4662 case Instruction::SRem:
4663 case Instruction::URem:
4664 return mayDivideByZero(*I);
4665 }
4666 return false;
4667}
4668
4669bool LoopVectorizationCostModel::interleavedAccessCanBeWidened(
4670 Instruction *I, ElementCount VF) {
4671 assert(isAccessInterleaved(I) && "Expecting interleaved access.")(static_cast <bool> (isAccessInterleaved(I) && "Expecting interleaved access."
) ? void (0) : __assert_fail ("isAccessInterleaved(I) && \"Expecting interleaved access.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4671, __extension__
__PRETTY_FUNCTION__))
;
4672 assert(getWideningDecision(I, VF) == CM_Unknown &&(static_cast <bool> (getWideningDecision(I, VF) == CM_Unknown
&& "Decision should not be set yet.") ? void (0) : __assert_fail
("getWideningDecision(I, VF) == CM_Unknown && \"Decision should not be set yet.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4673, __extension__
__PRETTY_FUNCTION__))
4673 "Decision should not be set yet.")(static_cast <bool> (getWideningDecision(I, VF) == CM_Unknown
&& "Decision should not be set yet.") ? void (0) : __assert_fail
("getWideningDecision(I, VF) == CM_Unknown && \"Decision should not be set yet.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4673, __extension__
__PRETTY_FUNCTION__))
;
4674 auto *Group = getInterleavedAccessGroup(I);
4675 assert(Group && "Must have a group.")(static_cast <bool> (Group && "Must have a group."
) ? void (0) : __assert_fail ("Group && \"Must have a group.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4675, __extension__
__PRETTY_FUNCTION__))
;
4676
4677 // If the instruction's allocated size doesn't equal it's type size, it
4678 // requires padding and will be scalarized.
4679 auto &DL = I->getModule()->getDataLayout();
4680 auto *ScalarTy = getLoadStoreType(I);
4681 if (hasIrregularType(ScalarTy, DL))
4682 return false;
4683
4684 // Check if masking is required.
4685 // A Group may need masking for one of two reasons: it resides in a block that
4686 // needs predication, or it was decided to use masking to deal with gaps
4687 // (either a gap at the end of a load-access that may result in a speculative
4688 // load, or any gaps in a store-access).
4689 bool PredicatedAccessRequiresMasking =
4690 blockNeedsPredicationForAnyReason(I->getParent()) &&
4691 Legal->isMaskRequired(I);
4692 bool LoadAccessWithGapsRequiresEpilogMasking =
4693 isa<LoadInst>(I) && Group->requiresScalarEpilogue() &&
4694 !isScalarEpilogueAllowed();
4695 bool StoreAccessWithGapsRequiresMasking =
4696 isa<StoreInst>(I) && (Group->getNumMembers() < Group->getFactor());
4697 if (!PredicatedAccessRequiresMasking &&
4698 !LoadAccessWithGapsRequiresEpilogMasking &&
4699 !StoreAccessWithGapsRequiresMasking)
4700 return true;
4701
4702 // If masked interleaving is required, we expect that the user/target had
4703 // enabled it, because otherwise it either wouldn't have been created or
4704 // it should have been invalidated by the CostModel.
4705 assert(useMaskedInterleavedAccesses(TTI) &&(static_cast <bool> (useMaskedInterleavedAccesses(TTI) &&
"Masked interleave-groups for predicated accesses are not enabled."
) ? void (0) : __assert_fail ("useMaskedInterleavedAccesses(TTI) && \"Masked interleave-groups for predicated accesses are not enabled.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4706, __extension__
__PRETTY_FUNCTION__))
4706 "Masked interleave-groups for predicated accesses are not enabled.")(static_cast <bool> (useMaskedInterleavedAccesses(TTI) &&
"Masked interleave-groups for predicated accesses are not enabled."
) ? void (0) : __assert_fail ("useMaskedInterleavedAccesses(TTI) && \"Masked interleave-groups for predicated accesses are not enabled.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4706, __extension__
__PRETTY_FUNCTION__))
;
4707
4708 if (Group->isReverse())
4709 return false;
4710
4711 auto *Ty = getLoadStoreType(I);
4712 const Align Alignment = getLoadStoreAlignment(I);
4713 return isa<LoadInst>(I) ? TTI.isLegalMaskedLoad(Ty, Alignment)
4714 : TTI.isLegalMaskedStore(Ty, Alignment);
4715}
4716
4717bool LoopVectorizationCostModel::memoryInstructionCanBeWidened(
4718 Instruction *I, ElementCount VF) {
4719 // Get and ensure we have a valid memory instruction.
4720 assert((isa<LoadInst, StoreInst>(I)) && "Invalid memory instruction")(static_cast <bool> ((isa<LoadInst, StoreInst>(I)
) && "Invalid memory instruction") ? void (0) : __assert_fail
("(isa<LoadInst, StoreInst>(I)) && \"Invalid memory instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4720, __extension__
__PRETTY_FUNCTION__))
;
4721
4722 auto *Ptr = getLoadStorePointerOperand(I);
4723 auto *ScalarTy = getLoadStoreType(I);
4724
4725 // In order to be widened, the pointer should be consecutive, first of all.
4726 if (!Legal->isConsecutivePtr(ScalarTy, Ptr))
4727 return false;
4728
4729 // If the instruction is a store located in a predicated block, it will be
4730 // scalarized.
4731 if (isScalarWithPredication(I, VF))
4732 return false;
4733
4734 // If the instruction's allocated size doesn't equal it's type size, it
4735 // requires padding and will be scalarized.
4736 auto &DL = I->getModule()->getDataLayout();
4737 if (hasIrregularType(ScalarTy, DL))
4738 return false;
4739
4740 return true;
4741}
4742
4743void LoopVectorizationCostModel::collectLoopUniforms(ElementCount VF) {
4744 // We should not collect Uniforms more than once per VF. Right now,
4745 // this function is called from collectUniformsAndScalars(), which
4746 // already does this check. Collecting Uniforms for VF=1 does not make any
4747 // sense.
4748
4749 assert(VF.isVector() && Uniforms.find(VF) == Uniforms.end() &&(static_cast <bool> (VF.isVector() && Uniforms.
find(VF) == Uniforms.end() && "This function should not be visited twice for the same VF"
) ? void (0) : __assert_fail ("VF.isVector() && Uniforms.find(VF) == Uniforms.end() && \"This function should not be visited twice for the same VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4750, __extension__
__PRETTY_FUNCTION__))
4750 "This function should not be visited twice for the same VF")(static_cast <bool> (VF.isVector() && Uniforms.
find(VF) == Uniforms.end() && "This function should not be visited twice for the same VF"
) ? void (0) : __assert_fail ("VF.isVector() && Uniforms.find(VF) == Uniforms.end() && \"This function should not be visited twice for the same VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4750, __extension__
__PRETTY_FUNCTION__))
;
4751
4752 // Visit the list of Uniforms. If we'll not find any uniform value, we'll
4753 // not analyze again. Uniforms.count(VF) will return 1.
4754 Uniforms[VF].clear();
4755
4756 // We now know that the loop is vectorizable!
4757 // Collect instructions inside the loop that will remain uniform after
4758 // vectorization.
4759
4760 // Global values, params and instructions outside of current loop are out of
4761 // scope.
4762 auto isOutOfScope = [&](Value *V) -> bool {
4763 Instruction *I = dyn_cast<Instruction>(V);
4764 return (!I || !TheLoop->contains(I));
4765 };
4766
4767 // Worklist containing uniform instructions demanding lane 0.
4768 SetVector<Instruction *> Worklist;
4769 BasicBlock *Latch = TheLoop->getLoopLatch();
4770
4771 // Add uniform instructions demanding lane 0 to the worklist. Instructions
4772 // that are scalar with predication must not be considered uniform after
4773 // vectorization, because that would create an erroneous replicating region
4774 // where only a single instance out of VF should be formed.
4775 // TODO: optimize such seldom cases if found important, see PR40816.
4776 auto addToWorklistIfAllowed = [&](Instruction *I) -> void {
4777 if (isOutOfScope(I)) {
4778 LLVM_DEBUG(dbgs() << "LV: Found not uniform due to scope: "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found not uniform due to scope: "
<< *I << "\n"; } } while (false)
4779 << *I << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found not uniform due to scope: "
<< *I << "\n"; } } while (false)
;
4780 return;
4781 }
4782 if (isScalarWithPredication(I, VF)) {
4783 LLVM_DEBUG(dbgs() << "LV: Found not uniform being ScalarWithPredication: "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found not uniform being ScalarWithPredication: "
<< *I << "\n"; } } while (false)
4784 << *I << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found not uniform being ScalarWithPredication: "
<< *I << "\n"; } } while (false)
;
4785 return;
4786 }
4787 LLVM_DEBUG(dbgs() << "LV: Found uniform instruction: " << *I << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found uniform instruction: "
<< *I << "\n"; } } while (false)
;
4788 Worklist.insert(I);
4789 };
4790
4791 // Start with the conditional branch. If the branch condition is an
4792 // instruction contained in the loop that is only used by the branch, it is
4793 // uniform.
4794 auto *Cmp = dyn_cast<Instruction>(Latch->getTerminator()->getOperand(0));
4795 if (Cmp && TheLoop->contains(Cmp) && Cmp->hasOneUse())
4796 addToWorklistIfAllowed(Cmp);
4797
4798 auto isUniformDecision = [&](Instruction *I, ElementCount VF) {
4799 InstWidening WideningDecision = getWideningDecision(I, VF);
4800 assert(WideningDecision != CM_Unknown &&(static_cast <bool> (WideningDecision != CM_Unknown &&
"Widening decision should be ready at this moment") ? void (
0) : __assert_fail ("WideningDecision != CM_Unknown && \"Widening decision should be ready at this moment\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4801, __extension__
__PRETTY_FUNCTION__))
4801 "Widening decision should be ready at this moment")(static_cast <bool> (WideningDecision != CM_Unknown &&
"Widening decision should be ready at this moment") ? void (
0) : __assert_fail ("WideningDecision != CM_Unknown && \"Widening decision should be ready at this moment\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4801, __extension__
__PRETTY_FUNCTION__))
;
4802
4803 // A uniform memory op is itself uniform. We exclude uniform stores
4804 // here as they demand the last lane, not the first one.
4805 if (isa<LoadInst>(I) && Legal->isUniformMemOp(*I)) {
4806 assert(WideningDecision == CM_Scalarize)(static_cast <bool> (WideningDecision == CM_Scalarize) ?
void (0) : __assert_fail ("WideningDecision == CM_Scalarize"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4806, __extension__
__PRETTY_FUNCTION__))
;
4807 return true;
4808 }
4809
4810 return (WideningDecision == CM_Widen ||
4811 WideningDecision == CM_Widen_Reverse ||
4812 WideningDecision == CM_Interleave);
4813 };
4814
4815
4816 // Returns true if Ptr is the pointer operand of a memory access instruction
4817 // I, and I is known to not require scalarization.
4818 auto isVectorizedMemAccessUse = [&](Instruction *I, Value *Ptr) -> bool {
4819 return getLoadStorePointerOperand(I) == Ptr && isUniformDecision(I, VF);
4820 };
4821
4822 // Holds a list of values which are known to have at least one uniform use.
4823 // Note that there may be other uses which aren't uniform. A "uniform use"
4824 // here is something which only demands lane 0 of the unrolled iterations;
4825 // it does not imply that all lanes produce the same value (e.g. this is not
4826 // the usual meaning of uniform)
4827 SetVector<Value *> HasUniformUse;
4828
4829 // Scan the loop for instructions which are either a) known to have only
4830 // lane 0 demanded or b) are uses which demand only lane 0 of their operand.
4831 for (auto *BB : TheLoop->blocks())
4832 for (auto &I : *BB) {
4833 if (IntrinsicInst *II = dyn_cast<IntrinsicInst>(&I)) {
4834 switch (II->getIntrinsicID()) {
4835 case Intrinsic::sideeffect:
4836 case Intrinsic::experimental_noalias_scope_decl:
4837 case Intrinsic::assume:
4838 case Intrinsic::lifetime_start:
4839 case Intrinsic::lifetime_end:
4840 if (TheLoop->hasLoopInvariantOperands(&I))
4841 addToWorklistIfAllowed(&I);
4842 break;
4843 default:
4844 break;
4845 }
4846 }
4847
4848 // ExtractValue instructions must be uniform, because the operands are
4849 // known to be loop-invariant.
4850 if (auto *EVI = dyn_cast<ExtractValueInst>(&I)) {
4851 assert(isOutOfScope(EVI->getAggregateOperand()) &&(static_cast <bool> (isOutOfScope(EVI->getAggregateOperand
()) && "Expected aggregate value to be loop invariant"
) ? void (0) : __assert_fail ("isOutOfScope(EVI->getAggregateOperand()) && \"Expected aggregate value to be loop invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4852, __extension__
__PRETTY_FUNCTION__))
4852 "Expected aggregate value to be loop invariant")(static_cast <bool> (isOutOfScope(EVI->getAggregateOperand
()) && "Expected aggregate value to be loop invariant"
) ? void (0) : __assert_fail ("isOutOfScope(EVI->getAggregateOperand()) && \"Expected aggregate value to be loop invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4852, __extension__
__PRETTY_FUNCTION__))
;
4853 addToWorklistIfAllowed(EVI);
4854 continue;
4855 }
4856
4857 // If there's no pointer operand, there's nothing to do.
4858 auto *Ptr = getLoadStorePointerOperand(&I);
4859 if (!Ptr)
4860 continue;
4861
4862 // A uniform memory op is itself uniform. We exclude uniform stores
4863 // here as they demand the last lane, not the first one.
4864 if (isa<LoadInst>(I) && Legal->isUniformMemOp(I))
4865 addToWorklistIfAllowed(&I);
4866
4867 if (isUniformDecision(&I, VF)) {
4868 assert(isVectorizedMemAccessUse(&I, Ptr) && "consistency check")(static_cast <bool> (isVectorizedMemAccessUse(&I, Ptr
) && "consistency check") ? void (0) : __assert_fail (
"isVectorizedMemAccessUse(&I, Ptr) && \"consistency check\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 4868, __extension__
__PRETTY_FUNCTION__))
;
4869 HasUniformUse.insert(Ptr);
4870 }
4871 }
4872
4873 // Add to the worklist any operands which have *only* uniform (e.g. lane 0
4874 // demanding) users. Since loops are assumed to be in LCSSA form, this
4875 // disallows uses outside the loop as well.
4876 for (auto *V : HasUniformUse) {
4877 if (isOutOfScope(V))
4878 continue;
4879 auto *I = cast<Instruction>(V);
4880 auto UsersAreMemAccesses =
4881 llvm::all_of(I->users(), [&](User *U) -> bool {
4882 return isVectorizedMemAccessUse(cast<Instruction>(U), V);
4883 });
4884 if (UsersAreMemAccesses)
4885 addToWorklistIfAllowed(I);
4886 }
4887
4888 // Expand Worklist in topological order: whenever a new instruction
4889 // is added , its users should be already inside Worklist. It ensures
4890 // a uniform instruction will only be used by uniform instructions.
4891 unsigned idx = 0;
4892 while (idx != Worklist.size()) {
4893 Instruction *I = Worklist[idx++];
4894
4895 for (auto OV : I->operand_values()) {
4896 // isOutOfScope operands cannot be uniform instructions.
4897 if (isOutOfScope(OV))
4898 continue;
4899 // First order recurrence Phi's should typically be considered
4900 // non-uniform.
4901 auto *OP = dyn_cast<PHINode>(OV);
4902 if (OP && Legal->isFirstOrderRecurrence(OP))
4903 continue;
4904 // If all the users of the operand are uniform, then add the
4905 // operand into the uniform worklist.
4906 auto *OI = cast<Instruction>(OV);
4907 if (llvm::all_of(OI->users(), [&](User *U) -> bool {
4908 auto *J = cast<Instruction>(U);
4909 return Worklist.count(J) || isVectorizedMemAccessUse(J, OI);
4910 }))
4911 addToWorklistIfAllowed(OI);
4912 }
4913 }
4914
4915 // For an instruction to be added into Worklist above, all its users inside
4916 // the loop should also be in Worklist. However, this condition cannot be
4917 // true for phi nodes that form a cyclic dependence. We must process phi
4918 // nodes separately. An induction variable will remain uniform if all users
4919 // of the induction variable and induction variable update remain uniform.
4920 // The code below handles both pointer and non-pointer induction variables.
4921 for (auto &Induction : Legal->getInductionVars()) {
4922 auto *Ind = Induction.first;
4923 auto *IndUpdate = cast<Instruction>(Ind->getIncomingValueForBlock(Latch));
4924
4925 // Determine if all users of the induction variable are uniform after
4926 // vectorization.
4927 auto UniformInd = llvm::all_of(Ind->users(), [&](User *U) -> bool {
4928 auto *I = cast<Instruction>(U);
4929 return I == IndUpdate || !TheLoop->contains(I) || Worklist.count(I) ||
4930 isVectorizedMemAccessUse(I, Ind);
4931 });
4932 if (!UniformInd)
4933 continue;
4934
4935 // Determine if all users of the induction variable update instruction are
4936 // uniform after vectorization.
4937 auto UniformIndUpdate =
4938 llvm::all_of(IndUpdate->users(), [&](User *U) -> bool {
4939 auto *I = cast<Instruction>(U);
4940 return I == Ind || !TheLoop->contains(I) || Worklist.count(I) ||
4941 isVectorizedMemAccessUse(I, IndUpdate);
4942 });
4943 if (!UniformIndUpdate)
4944 continue;
4945
4946 // The induction variable and its update instruction will remain uniform.
4947 addToWorklistIfAllowed(Ind);
4948 addToWorklistIfAllowed(IndUpdate);
4949 }
4950
4951 Uniforms[VF].insert(Worklist.begin(), Worklist.end());
4952}
4953
4954bool LoopVectorizationCostModel::runtimeChecksRequired() {
4955 LLVM_DEBUG(dbgs() << "LV: Performing code size checks.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Performing code size checks.\n"
; } } while (false)
;
4956
4957 if (Legal->getRuntimePointerChecking()->Need) {
4958 reportVectorizationFailure("Runtime ptr check is required with -Os/-Oz",
4959 "runtime pointer checks needed. Enable vectorization of this "
4960 "loop with '#pragma clang loop vectorize(enable)' when "
4961 "compiling with -Os/-Oz",
4962 "CantVersionLoopWithOptForSize", ORE, TheLoop);
4963 return true;
4964 }
4965
4966 if (!PSE.getPredicate().isAlwaysTrue()) {
4967 reportVectorizationFailure("Runtime SCEV check is required with -Os/-Oz",
4968 "runtime SCEV checks needed. Enable vectorization of this "
4969 "loop with '#pragma clang loop vectorize(enable)' when "
4970 "compiling with -Os/-Oz",
4971 "CantVersionLoopWithOptForSize", ORE, TheLoop);
4972 return true;
4973 }
4974
4975 // FIXME: Avoid specializing for stride==1 instead of bailing out.
4976 if (!Legal->getLAI()->getSymbolicStrides().empty()) {
4977 reportVectorizationFailure("Runtime stride check for small trip count",
4978 "runtime stride == 1 checks needed. Enable vectorization of "
4979 "this loop without such check by compiling with -Os/-Oz",
4980 "CantVersionLoopWithOptForSize", ORE, TheLoop);
4981 return true;
4982 }
4983
4984 return false;
4985}
4986
4987ElementCount
4988LoopVectorizationCostModel::getMaxLegalScalableVF(unsigned MaxSafeElements) {
4989 if (!TTI.supportsScalableVectors() && !ForceTargetSupportsScalableVectors)
4990 return ElementCount::getScalable(0);
4991
4992 if (Hints->isScalableVectorizationDisabled()) {
4993 reportVectorizationInfo("Scalable vectorization is explicitly disabled",
4994 "ScalableVectorizationDisabled", ORE, TheLoop);
4995 return ElementCount::getScalable(0);
4996 }
4997
4998 LLVM_DEBUG(dbgs() << "LV: Scalable vectorization is available\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Scalable vectorization is available\n"
; } } while (false)
;
4999
5000 auto MaxScalableVF = ElementCount::getScalable(
5001 std::numeric_limits<ElementCount::ScalarTy>::max());
5002
5003 // Test that the loop-vectorizer can legalize all operations for this MaxVF.
5004 // FIXME: While for scalable vectors this is currently sufficient, this should
5005 // be replaced by a more detailed mechanism that filters out specific VFs,
5006 // instead of invalidating vectorization for a whole set of VFs based on the
5007 // MaxVF.
5008
5009 // Disable scalable vectorization if the loop contains unsupported reductions.
5010 if (!canVectorizeReductions(MaxScalableVF)) {
5011 reportVectorizationInfo(
5012 "Scalable vectorization not supported for the reduction "
5013 "operations found in this loop.",
5014 "ScalableVFUnfeasible", ORE, TheLoop);
5015 return ElementCount::getScalable(0);
5016 }
5017
5018 // Disable scalable vectorization if the loop contains any instructions
5019 // with element types not supported for scalable vectors.
5020 if (any_of(ElementTypesInLoop, [&](Type *Ty) {
5021 return !Ty->isVoidTy() &&
5022 !this->TTI.isElementTypeLegalForScalableVector(Ty);
5023 })) {
5024 reportVectorizationInfo("Scalable vectorization is not supported "
5025 "for all element types found in this loop.",
5026 "ScalableVFUnfeasible", ORE, TheLoop);
5027 return ElementCount::getScalable(0);
5028 }
5029
5030 if (Legal->isSafeForAnyVectorWidth())
5031 return MaxScalableVF;
5032
5033 // Limit MaxScalableVF by the maximum safe dependence distance.
5034 Optional<unsigned> MaxVScale = TTI.getMaxVScale();
5035 if (!MaxVScale && TheFunction->hasFnAttribute(Attribute::VScaleRange))
5036 MaxVScale =
5037 TheFunction->getFnAttribute(Attribute::VScaleRange).getVScaleRangeMax();
5038 MaxScalableVF = ElementCount::getScalable(
5039 MaxVScale ? (MaxSafeElements / MaxVScale.getValue()) : 0);
5040 if (!MaxScalableVF)
5041 reportVectorizationInfo(
5042 "Max legal vector width too small, scalable vectorization "
5043 "unfeasible.",
5044 "ScalableVFUnfeasible", ORE, TheLoop);
5045
5046 return MaxScalableVF;
5047}
5048
5049FixedScalableVFPair LoopVectorizationCostModel::computeFeasibleMaxVF(
5050 unsigned ConstTripCount, ElementCount UserVF, bool FoldTailByMasking) {
5051 MinBWs = computeMinimumValueSizes(TheLoop->getBlocks(), *DB, &TTI);
5052 unsigned SmallestType, WidestType;
5053 std::tie(SmallestType, WidestType) = getSmallestAndWidestTypes();
5054
5055 // Get the maximum safe dependence distance in bits computed by LAA.
5056 // It is computed by MaxVF * sizeOf(type) * 8, where type is taken from
5057 // the memory accesses that is most restrictive (involved in the smallest
5058 // dependence distance).
5059 unsigned MaxSafeElements =
5060 PowerOf2Floor(Legal->getMaxSafeVectorWidthInBits() / WidestType);
5061
5062 auto MaxSafeFixedVF = ElementCount::getFixed(MaxSafeElements);
5063 auto MaxSafeScalableVF = getMaxLegalScalableVF(MaxSafeElements);
5064
5065 LLVM_DEBUG(dbgs() << "LV: The max safe fixed VF is: " << MaxSafeFixedVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The max safe fixed VF is: "
<< MaxSafeFixedVF << ".\n"; } } while (false)
5066 << ".\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The max safe fixed VF is: "
<< MaxSafeFixedVF << ".\n"; } } while (false)
;
5067 LLVM_DEBUG(dbgs() << "LV: The max safe scalable VF is: " << MaxSafeScalableVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The max safe scalable VF is: "
<< MaxSafeScalableVF << ".\n"; } } while (false)
5068 << ".\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The max safe scalable VF is: "
<< MaxSafeScalableVF << ".\n"; } } while (false)
;
5069
5070 // First analyze the UserVF, fall back if the UserVF should be ignored.
5071 if (UserVF) {
5072 auto MaxSafeUserVF =
5073 UserVF.isScalable() ? MaxSafeScalableVF : MaxSafeFixedVF;
5074
5075 if (ElementCount::isKnownLE(UserVF, MaxSafeUserVF)) {
5076 // If `VF=vscale x N` is safe, then so is `VF=N`
5077 if (UserVF.isScalable())
5078 return FixedScalableVFPair(
5079 ElementCount::getFixed(UserVF.getKnownMinValue()), UserVF);
5080 else
5081 return UserVF;
5082 }
5083
5084 assert(ElementCount::isKnownGT(UserVF, MaxSafeUserVF))(static_cast <bool> (ElementCount::isKnownGT(UserVF, MaxSafeUserVF
)) ? void (0) : __assert_fail ("ElementCount::isKnownGT(UserVF, MaxSafeUserVF)"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5084, __extension__
__PRETTY_FUNCTION__))
;
5085
5086 // Only clamp if the UserVF is not scalable. If the UserVF is scalable, it
5087 // is better to ignore the hint and let the compiler choose a suitable VF.
5088 if (!UserVF.isScalable()) {
5089 LLVM_DEBUG(dbgs() << "LV: User VF=" << UserVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: User VF=" <<
UserVF << " is unsafe, clamping to max safe VF=" <<
MaxSafeFixedVF << ".\n"; } } while (false)
5090 << " is unsafe, clamping to max safe VF="do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: User VF=" <<
UserVF << " is unsafe, clamping to max safe VF=" <<
MaxSafeFixedVF << ".\n"; } } while (false)
5091 << MaxSafeFixedVF << ".\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: User VF=" <<
UserVF << " is unsafe, clamping to max safe VF=" <<
MaxSafeFixedVF << ".\n"; } } while (false)
;
5092 ORE->emit([&]() {
5093 return OptimizationRemarkAnalysis(DEBUG_TYPE"loop-vectorize", "VectorizationFactor",
5094 TheLoop->getStartLoc(),
5095 TheLoop->getHeader())
5096 << "User-specified vectorization factor "
5097 << ore::NV("UserVectorizationFactor", UserVF)
5098 << " is unsafe, clamping to maximum safe vectorization factor "
5099 << ore::NV("VectorizationFactor", MaxSafeFixedVF);
5100 });
5101 return MaxSafeFixedVF;
5102 }
5103
5104 if (!TTI.supportsScalableVectors() && !ForceTargetSupportsScalableVectors) {
5105 LLVM_DEBUG(dbgs() << "LV: User VF=" << UserVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: User VF=" <<
UserVF << " is ignored because scalable vectors are not "
"available.\n"; } } while (false)
5106 << " is ignored because scalable vectors are not "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: User VF=" <<
UserVF << " is ignored because scalable vectors are not "
"available.\n"; } } while (false)
5107 "available.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: User VF=" <<
UserVF << " is ignored because scalable vectors are not "
"available.\n"; } } while (false)
;
5108 ORE->emit([&]() {
5109 return OptimizationRemarkAnalysis(DEBUG_TYPE"loop-vectorize", "VectorizationFactor",
5110 TheLoop->getStartLoc(),
5111 TheLoop->getHeader())
5112 << "User-specified vectorization factor "
5113 << ore::NV("UserVectorizationFactor", UserVF)
5114 << " is ignored because the target does not support scalable "
5115 "vectors. The compiler will pick a more suitable value.";
5116 });
5117 } else {
5118 LLVM_DEBUG(dbgs() << "LV: User VF=" << UserVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: User VF=" <<
UserVF << " is unsafe. Ignoring scalable UserVF.\n"; }
} while (false)
5119 << " is unsafe. Ignoring scalable UserVF.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: User VF=" <<
UserVF << " is unsafe. Ignoring scalable UserVF.\n"; }
} while (false)
;
5120 ORE->emit([&]() {
5121 return OptimizationRemarkAnalysis(DEBUG_TYPE"loop-vectorize", "VectorizationFactor",
5122 TheLoop->getStartLoc(),
5123 TheLoop->getHeader())
5124 << "User-specified vectorization factor "
5125 << ore::NV("UserVectorizationFactor", UserVF)
5126 << " is unsafe. Ignoring the hint to let the compiler pick a "
5127 "more suitable value.";
5128 });
5129 }
5130 }
5131
5132 LLVM_DEBUG(dbgs() << "LV: The Smallest and Widest types: " << SmallestTypedo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The Smallest and Widest types: "
<< SmallestType << " / " << WidestType <<
" bits.\n"; } } while (false)
5133 << " / " << WidestType << " bits.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The Smallest and Widest types: "
<< SmallestType << " / " << WidestType <<
" bits.\n"; } } while (false)
;
5134
5135 FixedScalableVFPair Result(ElementCount::getFixed(1),
5136 ElementCount::getScalable(0));
5137 if (auto MaxVF =
5138 getMaximizedVFForTarget(ConstTripCount, SmallestType, WidestType,
5139 MaxSafeFixedVF, FoldTailByMasking))
5140 Result.FixedVF = MaxVF;
5141
5142 if (auto MaxVF =
5143 getMaximizedVFForTarget(ConstTripCount, SmallestType, WidestType,
5144 MaxSafeScalableVF, FoldTailByMasking))
5145 if (MaxVF.isScalable()) {
5146 Result.ScalableVF = MaxVF;
5147 LLVM_DEBUG(dbgs() << "LV: Found feasible scalable VF = " << MaxVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found feasible scalable VF = "
<< MaxVF << "\n"; } } while (false)
5148 << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found feasible scalable VF = "
<< MaxVF << "\n"; } } while (false)
;
5149 }
5150
5151 return Result;
5152}
5153
5154FixedScalableVFPair
5155LoopVectorizationCostModel::computeMaxVF(ElementCount UserVF, unsigned UserIC) {
5156 if (Legal->getRuntimePointerChecking()->Need && TTI.hasBranchDivergence()) {
5157 // TODO: It may by useful to do since it's still likely to be dynamically
5158 // uniform if the target can skip.
5159 reportVectorizationFailure(
5160 "Not inserting runtime ptr check for divergent target",
5161 "runtime pointer checks needed. Not enabled for divergent target",
5162 "CantVersionLoopWithDivergentTarget", ORE, TheLoop);
5163 return FixedScalableVFPair::getNone();
5164 }
5165
5166 unsigned TC = PSE.getSE()->getSmallConstantTripCount(TheLoop);
5167 LLVM_DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found trip count: "
<< TC << '\n'; } } while (false)
;
5168 if (TC == 1) {
5169 reportVectorizationFailure("Single iteration (non) loop",
5170 "loop trip count is one, irrelevant for vectorization",
5171 "SingleIterationLoop", ORE, TheLoop);
5172 return FixedScalableVFPair::getNone();
5173 }
5174
5175 switch (ScalarEpilogueStatus) {
5176 case CM_ScalarEpilogueAllowed:
5177 return computeFeasibleMaxVF(TC, UserVF, false);
5178 case CM_ScalarEpilogueNotAllowedUsePredicate:
5179 LLVM_FALLTHROUGH[[gnu::fallthrough]];
5180 case CM_ScalarEpilogueNotNeededUsePredicate:
5181 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: vector predicate hint/switch found.\n"
<< "LV: Not allowing scalar epilogue, creating predicated "
<< "vector loop.\n"; } } while (false)
5182 dbgs() << "LV: vector predicate hint/switch found.\n"do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: vector predicate hint/switch found.\n"
<< "LV: Not allowing scalar epilogue, creating predicated "
<< "vector loop.\n"; } } while (false)
5183 << "LV: Not allowing scalar epilogue, creating predicated "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: vector predicate hint/switch found.\n"
<< "LV: Not allowing scalar epilogue, creating predicated "
<< "vector loop.\n"; } } while (false)
5184 << "vector loop.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: vector predicate hint/switch found.\n"
<< "LV: Not allowing scalar epilogue, creating predicated "
<< "vector loop.\n"; } } while (false)
;
5185 break;
5186 case CM_ScalarEpilogueNotAllowedLowTripLoop:
5187 // fallthrough as a special case of OptForSize
5188 case CM_ScalarEpilogueNotAllowedOptSize:
5189 if (ScalarEpilogueStatus == CM_ScalarEpilogueNotAllowedOptSize)
5190 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not allowing scalar epilogue due to -Os/-Oz.\n"
; } } while (false)
5191 dbgs() << "LV: Not allowing scalar epilogue due to -Os/-Oz.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not allowing scalar epilogue due to -Os/-Oz.\n"
; } } while (false)
;
5192 else
5193 LLVM_DEBUG(dbgs() << "LV: Not allowing scalar epilogue due to low trip "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not allowing scalar epilogue due to low trip "
<< "count.\n"; } } while (false)
5194 << "count.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not allowing scalar epilogue due to low trip "
<< "count.\n"; } } while (false)
;
5195
5196 // Bail if runtime checks are required, which are not good when optimising
5197 // for size.
5198 if (runtimeChecksRequired())
5199 return FixedScalableVFPair::getNone();
5200
5201 break;
5202 }
5203
5204 // The only loops we can vectorize without a scalar epilogue, are loops with
5205 // a bottom-test and a single exiting block. We'd have to handle the fact
5206 // that not every instruction executes on the last iteration. This will
5207 // require a lane mask which varies through the vector loop body. (TODO)
5208 if (TheLoop->getExitingBlock() != TheLoop->getLoopLatch()) {
5209 // If there was a tail-folding hint/switch, but we can't fold the tail by
5210 // masking, fallback to a vectorization with a scalar epilogue.
5211 if (ScalarEpilogueStatus == CM_ScalarEpilogueNotNeededUsePredicate) {
5212 LLVM_DEBUG(dbgs() << "LV: Cannot fold tail by masking: vectorize with a "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Cannot fold tail by masking: vectorize with a "
"scalar epilogue instead.\n"; } } while (false)
5213 "scalar epilogue instead.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Cannot fold tail by masking: vectorize with a "
"scalar epilogue instead.\n"; } } while (false)
;
5214 ScalarEpilogueStatus = CM_ScalarEpilogueAllowed;
5215 return computeFeasibleMaxVF(TC, UserVF, false);
5216 }
5217 return FixedScalableVFPair::getNone();
5218 }
5219
5220 // Now try the tail folding
5221
5222 // Invalidate interleave groups that require an epilogue if we can't mask
5223 // the interleave-group.
5224 if (!useMaskedInterleavedAccesses(TTI)) {
5225 assert(WideningDecisions.empty() && Uniforms.empty() && Scalars.empty() &&(static_cast <bool> (WideningDecisions.empty() &&
Uniforms.empty() && Scalars.empty() && "No decisions should have been taken at this point"
) ? void (0) : __assert_fail ("WideningDecisions.empty() && Uniforms.empty() && Scalars.empty() && \"No decisions should have been taken at this point\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5226, __extension__
__PRETTY_FUNCTION__))
5226 "No decisions should have been taken at this point")(static_cast <bool> (WideningDecisions.empty() &&
Uniforms.empty() && Scalars.empty() && "No decisions should have been taken at this point"
) ? void (0) : __assert_fail ("WideningDecisions.empty() && Uniforms.empty() && Scalars.empty() && \"No decisions should have been taken at this point\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5226, __extension__
__PRETTY_FUNCTION__))
;
5227 // Note: There is no need to invalidate any cost modeling decisions here, as
5228 // non where taken so far.
5229 InterleaveInfo.invalidateGroupsRequiringScalarEpilogue();
5230 }
5231
5232 FixedScalableVFPair MaxFactors = computeFeasibleMaxVF(TC, UserVF, true);
5233 // Avoid tail folding if the trip count is known to be a multiple of any VF
5234 // we chose.
5235 // FIXME: The condition below pessimises the case for fixed-width vectors,
5236 // when scalable VFs are also candidates for vectorization.
5237 if (MaxFactors.FixedVF.isVector() && !MaxFactors.ScalableVF) {
5238 ElementCount MaxFixedVF = MaxFactors.FixedVF;
5239 assert((UserVF.isNonZero() || isPowerOf2_32(MaxFixedVF.getFixedValue())) &&(static_cast <bool> ((UserVF.isNonZero() || isPowerOf2_32
(MaxFixedVF.getFixedValue())) && "MaxFixedVF must be a power of 2"
) ? void (0) : __assert_fail ("(UserVF.isNonZero() || isPowerOf2_32(MaxFixedVF.getFixedValue())) && \"MaxFixedVF must be a power of 2\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5240, __extension__
__PRETTY_FUNCTION__))
5240 "MaxFixedVF must be a power of 2")(static_cast <bool> ((UserVF.isNonZero() || isPowerOf2_32
(MaxFixedVF.getFixedValue())) && "MaxFixedVF must be a power of 2"
) ? void (0) : __assert_fail ("(UserVF.isNonZero() || isPowerOf2_32(MaxFixedVF.getFixedValue())) && \"MaxFixedVF must be a power of 2\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5240, __extension__
__PRETTY_FUNCTION__))
;
5241 unsigned MaxVFtimesIC = UserIC ? MaxFixedVF.getFixedValue() * UserIC
5242 : MaxFixedVF.getFixedValue();
5243 ScalarEvolution *SE = PSE.getSE();
5244 const SCEV *BackedgeTakenCount = PSE.getBackedgeTakenCount();
5245 const SCEV *ExitCount = SE->getAddExpr(
5246 BackedgeTakenCount, SE->getOne(BackedgeTakenCount->getType()));
5247 const SCEV *Rem = SE->getURemExpr(
5248 SE->applyLoopGuards(ExitCount, TheLoop),
5249 SE->getConstant(BackedgeTakenCount->getType(), MaxVFtimesIC));
5250 if (Rem->isZero()) {
5251 // Accept MaxFixedVF if we do not have a tail.
5252 LLVM_DEBUG(dbgs() << "LV: No tail will remain for any chosen VF.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: No tail will remain for any chosen VF.\n"
; } } while (false)
;
5253 return MaxFactors;
5254 }
5255 }
5256
5257 // For scalable vectors don't use tail folding for low trip counts or
5258 // optimizing for code size. We only permit this if the user has explicitly
5259 // requested it.
5260 if (ScalarEpilogueStatus != CM_ScalarEpilogueNotNeededUsePredicate &&
5261 ScalarEpilogueStatus != CM_ScalarEpilogueNotAllowedUsePredicate &&
5262 MaxFactors.ScalableVF.isVector())
5263 MaxFactors.ScalableVF = ElementCount::getScalable(0);
5264
5265 // If we don't know the precise trip count, or if the trip count that we
5266 // found modulo the vectorization factor is not zero, try to fold the tail
5267 // by masking.
5268 // FIXME: look for a smaller MaxVF that does divide TC rather than masking.
5269 if (Legal->prepareToFoldTailByMasking()) {
5270 FoldTailByMasking = true;
5271 return MaxFactors;
5272 }
5273
5274 // If there was a tail-folding hint/switch, but we can't fold the tail by
5275 // masking, fallback to a vectorization with a scalar epilogue.
5276 if (ScalarEpilogueStatus == CM_ScalarEpilogueNotNeededUsePredicate) {
5277 LLVM_DEBUG(dbgs() << "LV: Cannot fold tail by masking: vectorize with a "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Cannot fold tail by masking: vectorize with a "
"scalar epilogue instead.\n"; } } while (false)
5278 "scalar epilogue instead.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Cannot fold tail by masking: vectorize with a "
"scalar epilogue instead.\n"; } } while (false)
;
5279 ScalarEpilogueStatus = CM_ScalarEpilogueAllowed;
5280 return MaxFactors;
5281 }
5282
5283 if (ScalarEpilogueStatus == CM_ScalarEpilogueNotAllowedUsePredicate) {
5284 LLVM_DEBUG(dbgs() << "LV: Can't fold tail by masking: don't vectorize\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Can't fold tail by masking: don't vectorize\n"
; } } while (false)
;
5285 return FixedScalableVFPair::getNone();
5286 }
5287
5288 if (TC == 0) {
5289 reportVectorizationFailure(
5290 "Unable to calculate the loop count due to complex control flow",
5291 "unable to calculate the loop count due to complex control flow",
5292 "UnknownLoopCountComplexCFG", ORE, TheLoop);
5293 return FixedScalableVFPair::getNone();
5294 }
5295
5296 reportVectorizationFailure(
5297 "Cannot optimize for size and vectorize at the same time.",
5298 "cannot optimize for size and vectorize at the same time. "
5299 "Enable vectorization of this loop with '#pragma clang loop "
5300 "vectorize(enable)' when compiling with -Os/-Oz",
5301 "NoTailLoopWithOptForSize", ORE, TheLoop);
5302 return FixedScalableVFPair::getNone();
5303}
5304
5305ElementCount LoopVectorizationCostModel::getMaximizedVFForTarget(
5306 unsigned ConstTripCount, unsigned SmallestType, unsigned WidestType,
5307 const ElementCount &MaxSafeVF, bool FoldTailByMasking) {
5308 bool ComputeScalableMaxVF = MaxSafeVF.isScalable();
5309 TypeSize WidestRegister = TTI.getRegisterBitWidth(
5310 ComputeScalableMaxVF ? TargetTransformInfo::RGK_ScalableVector
5311 : TargetTransformInfo::RGK_FixedWidthVector);
5312
5313 // Convenience function to return the minimum of two ElementCounts.
5314 auto MinVF = [](const ElementCount &LHS, const ElementCount &RHS) {
5315 assert((LHS.isScalable() == RHS.isScalable()) &&(static_cast <bool> ((LHS.isScalable() == RHS.isScalable
()) && "Scalable flags must match") ? void (0) : __assert_fail
("(LHS.isScalable() == RHS.isScalable()) && \"Scalable flags must match\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5316, __extension__
__PRETTY_FUNCTION__))
5316 "Scalable flags must match")(static_cast <bool> ((LHS.isScalable() == RHS.isScalable
()) && "Scalable flags must match") ? void (0) : __assert_fail
("(LHS.isScalable() == RHS.isScalable()) && \"Scalable flags must match\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5316, __extension__
__PRETTY_FUNCTION__))
;
5317 return ElementCount::isKnownLT(LHS, RHS) ? LHS : RHS;
5318 };
5319
5320 // Ensure MaxVF is a power of 2; the dependence distance bound may not be.
5321 // Note that both WidestRegister and WidestType may not be a powers of 2.
5322 auto MaxVectorElementCount = ElementCount::get(
5323 PowerOf2Floor(WidestRegister.getKnownMinSize() / WidestType),
5324 ComputeScalableMaxVF);
5325 MaxVectorElementCount = MinVF(MaxVectorElementCount, MaxSafeVF);
5326 LLVM_DEBUG(dbgs() << "LV: The Widest register safe to use is: "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The Widest register safe to use is: "
<< (MaxVectorElementCount * WidestType) << " bits.\n"
; } } while (false)
5327 << (MaxVectorElementCount * WidestType) << " bits.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The Widest register safe to use is: "
<< (MaxVectorElementCount * WidestType) << " bits.\n"
; } } while (false)
;
5328
5329 if (!MaxVectorElementCount) {
5330 LLVM_DEBUG(dbgs() << "LV: The target has no "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The target has no "
<< (ComputeScalableMaxVF ? "scalable" : "fixed") <<
" vector registers.\n"; } } while (false)
5331 << (ComputeScalableMaxVF ? "scalable" : "fixed")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The target has no "
<< (ComputeScalableMaxVF ? "scalable" : "fixed") <<
" vector registers.\n"; } } while (false)
5332 << " vector registers.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The target has no "
<< (ComputeScalableMaxVF ? "scalable" : "fixed") <<
" vector registers.\n"; } } while (false)
;
5333 return ElementCount::getFixed(1);
5334 }
5335
5336 const auto TripCountEC = ElementCount::getFixed(ConstTripCount);
5337 if (ConstTripCount &&
5338 ElementCount::isKnownLE(TripCountEC, MaxVectorElementCount) &&
5339 (!FoldTailByMasking || isPowerOf2_32(ConstTripCount))) {
5340 // If loop trip count (TC) is known at compile time there is no point in
5341 // choosing VF greater than TC (as done in the loop below). Select maximum
5342 // power of two which doesn't exceed TC.
5343 // If MaxVectorElementCount is scalable, we only fall back on a fixed VF
5344 // when the TC is less than or equal to the known number of lanes.
5345 auto ClampedConstTripCount = PowerOf2Floor(ConstTripCount);
5346 LLVM_DEBUG(dbgs() << "LV: Clamping the MaxVF to maximum power of two not "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Clamping the MaxVF to maximum power of two not "
"exceeding the constant trip count: " << ClampedConstTripCount
<< "\n"; } } while (false)
5347 "exceeding the constant trip count: "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Clamping the MaxVF to maximum power of two not "
"exceeding the constant trip count: " << ClampedConstTripCount
<< "\n"; } } while (false)
5348 << ClampedConstTripCount << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Clamping the MaxVF to maximum power of two not "
"exceeding the constant trip count: " << ClampedConstTripCount
<< "\n"; } } while (false)
;
5349 return ElementCount::getFixed(ClampedConstTripCount);
5350 }
5351
5352 ElementCount MaxVF = MaxVectorElementCount;
5353 if (TTI.shouldMaximizeVectorBandwidth() ||
5354 (MaximizeBandwidth && isScalarEpilogueAllowed())) {
5355 auto MaxVectorElementCountMaxBW = ElementCount::get(
5356 PowerOf2Floor(WidestRegister.getKnownMinSize() / SmallestType),
5357 ComputeScalableMaxVF);
5358 MaxVectorElementCountMaxBW = MinVF(MaxVectorElementCountMaxBW, MaxSafeVF);
5359
5360 // Collect all viable vectorization factors larger than the default MaxVF
5361 // (i.e. MaxVectorElementCount).
5362 SmallVector<ElementCount, 8> VFs;
5363 for (ElementCount VS = MaxVectorElementCount * 2;
5364 ElementCount::isKnownLE(VS, MaxVectorElementCountMaxBW); VS *= 2)
5365 VFs.push_back(VS);
5366
5367 // For each VF calculate its register usage.
5368 auto RUs = calculateRegisterUsage(VFs);
5369
5370 // Select the largest VF which doesn't require more registers than existing
5371 // ones.
5372 for (int i = RUs.size() - 1; i >= 0; --i) {
5373 bool Selected = true;
5374 for (auto &pair : RUs[i].MaxLocalUsers) {
5375 unsigned TargetNumRegisters = TTI.getNumberOfRegisters(pair.first);
5376 if (pair.second > TargetNumRegisters)
5377 Selected = false;
5378 }
5379 if (Selected) {
5380 MaxVF = VFs[i];
5381 break;
5382 }
5383 }
5384 if (ElementCount MinVF =
5385 TTI.getMinimumVF(SmallestType, ComputeScalableMaxVF)) {
5386 if (ElementCount::isKnownLT(MaxVF, MinVF)) {
5387 LLVM_DEBUG(dbgs() << "LV: Overriding calculated MaxVF(" << MaxVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Overriding calculated MaxVF("
<< MaxVF << ") with target's minimum: " <<
MinVF << '\n'; } } while (false)
5388 << ") with target's minimum: " << MinVF << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Overriding calculated MaxVF("
<< MaxVF << ") with target's minimum: " <<
MinVF << '\n'; } } while (false)
;
5389 MaxVF = MinVF;
5390 }
5391 }
5392 }
5393 return MaxVF;
5394}
5395
5396Optional<unsigned> LoopVectorizationCostModel::getVScaleForTuning() const {
5397 if (TheFunction->hasFnAttribute(Attribute::VScaleRange)) {
5398 auto Attr = TheFunction->getFnAttribute(Attribute::VScaleRange);
5399 auto Min = Attr.getVScaleRangeMin();
5400 auto Max = Attr.getVScaleRangeMax();
5401 if (Max && Min == Max)
5402 return Max;
5403 }
5404
5405 return TTI.getVScaleForTuning();
5406}
5407
5408bool LoopVectorizationCostModel::isMoreProfitable(
5409 const VectorizationFactor &A, const VectorizationFactor &B) const {
5410 InstructionCost CostA = A.Cost;
5411 InstructionCost CostB = B.Cost;
5412
5413 unsigned MaxTripCount = PSE.getSE()->getSmallConstantMaxTripCount(TheLoop);
5414
5415 if (!A.Width.isScalable() && !B.Width.isScalable() && FoldTailByMasking &&
5416 MaxTripCount) {
5417 // If we are folding the tail and the trip count is a known (possibly small)
5418 // constant, the trip count will be rounded up to an integer number of
5419 // iterations. The total cost will be PerIterationCost*ceil(TripCount/VF),
5420 // which we compare directly. When not folding the tail, the total cost will
5421 // be PerIterationCost*floor(TC/VF) + Scalar remainder cost, and so is
5422 // approximated with the per-lane cost below instead of using the tripcount
5423 // as here.
5424 auto RTCostA = CostA * divideCeil(MaxTripCount, A.Width.getFixedValue());
5425 auto RTCostB = CostB * divideCeil(MaxTripCount, B.Width.getFixedValue());
5426 return RTCostA < RTCostB;
5427 }
5428
5429 // Improve estimate for the vector width if it is scalable.
5430 unsigned EstimatedWidthA = A.Width.getKnownMinValue();
5431 unsigned EstimatedWidthB = B.Width.getKnownMinValue();
5432 if (Optional<unsigned> VScale = getVScaleForTuning()) {
5433 if (A.Width.isScalable())
5434 EstimatedWidthA *= VScale.getValue();
5435 if (B.Width.isScalable())
5436 EstimatedWidthB *= VScale.getValue();
5437 }
5438
5439 // Assume vscale may be larger than 1 (or the value being tuned for),
5440 // so that scalable vectorization is slightly favorable over fixed-width
5441 // vectorization.
5442 if (A.Width.isScalable() && !B.Width.isScalable())
5443 return (CostA * B.Width.getFixedValue()) <= (CostB * EstimatedWidthA);
5444
5445 // To avoid the need for FP division:
5446 // (CostA / A.Width) < (CostB / B.Width)
5447 // <=> (CostA * B.Width) < (CostB * A.Width)
5448 return (CostA * EstimatedWidthB) < (CostB * EstimatedWidthA);
5449}
5450
5451VectorizationFactor LoopVectorizationCostModel::selectVectorizationFactor(
5452 const ElementCountSet &VFCandidates) {
5453 InstructionCost ExpectedCost = expectedCost(ElementCount::getFixed(1)).first;
5454 LLVM_DEBUG(dbgs() << "LV: Scalar loop costs: " << ExpectedCost << ".\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Scalar loop costs: "
<< ExpectedCost << ".\n"; } } while (false)
;
5455 assert(ExpectedCost.isValid() && "Unexpected invalid cost for scalar loop")(static_cast <bool> (ExpectedCost.isValid() && "Unexpected invalid cost for scalar loop"
) ? void (0) : __assert_fail ("ExpectedCost.isValid() && \"Unexpected invalid cost for scalar loop\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5455, __extension__
__PRETTY_FUNCTION__))
;
5456 assert(VFCandidates.count(ElementCount::getFixed(1)) &&(static_cast <bool> (VFCandidates.count(ElementCount::getFixed
(1)) && "Expected Scalar VF to be a candidate") ? void
(0) : __assert_fail ("VFCandidates.count(ElementCount::getFixed(1)) && \"Expected Scalar VF to be a candidate\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5457, __extension__
__PRETTY_FUNCTION__))
5457 "Expected Scalar VF to be a candidate")(static_cast <bool> (VFCandidates.count(ElementCount::getFixed
(1)) && "Expected Scalar VF to be a candidate") ? void
(0) : __assert_fail ("VFCandidates.count(ElementCount::getFixed(1)) && \"Expected Scalar VF to be a candidate\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5457, __extension__
__PRETTY_FUNCTION__))
;
5458
5459 const VectorizationFactor ScalarCost(ElementCount::getFixed(1), ExpectedCost);
5460 VectorizationFactor ChosenFactor = ScalarCost;
5461
5462 bool ForceVectorization = Hints->getForce() == LoopVectorizeHints::FK_Enabled;
5463 if (ForceVectorization && VFCandidates.size() > 1) {
5464 // Ignore scalar width, because the user explicitly wants vectorization.
5465 // Initialize cost to max so that VF = 2 is, at least, chosen during cost
5466 // evaluation.
5467 ChosenFactor.Cost = InstructionCost::getMax();
5468 }
5469
5470 SmallVector<InstructionVFPair> InvalidCosts;
5471 for (const auto &i : VFCandidates) {
5472 // The cost for scalar VF=1 is already calculated, so ignore it.
5473 if (i.isScalar())
5474 continue;
5475
5476 VectorizationCostTy C = expectedCost(i, &InvalidCosts);
5477 VectorizationFactor Candidate(i, C.first);
5478
5479#ifndef NDEBUG
5480 unsigned AssumedMinimumVscale = 1;
5481 if (Optional<unsigned> VScale = getVScaleForTuning())
5482 AssumedMinimumVscale = VScale.getValue();
5483 unsigned Width =
5484 Candidate.Width.isScalable()
5485 ? Candidate.Width.getKnownMinValue() * AssumedMinimumVscale
5486 : Candidate.Width.getFixedValue();
5487 LLVM_DEBUG(dbgs() << "LV: Vector loop of width " << ido { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Vector loop of width "
<< i << " costs: " << (Candidate.Cost / Width
); } } while (false)
5488 << " costs: " << (Candidate.Cost / Width))do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Vector loop of width "
<< i << " costs: " << (Candidate.Cost / Width
); } } while (false)
;
5489 if (i.isScalable())
5490 LLVM_DEBUG(dbgs() << " (assuming a minimum vscale of "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << " (assuming a minimum vscale of "
<< AssumedMinimumVscale << ")"; } } while (false
)
5491 << AssumedMinimumVscale << ")")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << " (assuming a minimum vscale of "
<< AssumedMinimumVscale << ")"; } } while (false
)
;
5492 LLVM_DEBUG(dbgs() << ".\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << ".\n"; } } while (false
)
;
5493#endif
5494
5495 if (!C.second && !ForceVectorization) {
5496 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not considering vector loop of width "
<< i << " because it will not generate any vector instructions.\n"
; } } while (false)
5497 dbgs() << "LV: Not considering vector loop of width " << ido { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not considering vector loop of width "
<< i << " because it will not generate any vector instructions.\n"
; } } while (false)
5498 << " because it will not generate any vector instructions.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not considering vector loop of width "
<< i << " because it will not generate any vector instructions.\n"
; } } while (false)
;
5499 continue;
5500 }
5501
5502 // If profitable add it to ProfitableVF list.
5503 if (isMoreProfitable(Candidate, ScalarCost))
5504 ProfitableVFs.push_back(Candidate);
5505
5506 if (isMoreProfitable(Candidate, ChosenFactor))
5507 ChosenFactor = Candidate;
5508 }
5509
5510 // Emit a report of VFs with invalid costs in the loop.
5511 if (!InvalidCosts.empty()) {
5512 // Group the remarks per instruction, keeping the instruction order from
5513 // InvalidCosts.
5514 std::map<Instruction *, unsigned> Numbering;
5515 unsigned I = 0;
5516 for (auto &Pair : InvalidCosts)
5517 if (!Numbering.count(Pair.first))
5518 Numbering[Pair.first] = I++;
5519
5520 // Sort the list, first on instruction(number) then on VF.
5521 llvm::sort(InvalidCosts,
5522 [&Numbering](InstructionVFPair &A, InstructionVFPair &B) {
5523 if (Numbering[A.first] != Numbering[B.first])
5524 return Numbering[A.first] < Numbering[B.first];
5525 ElementCountComparator ECC;
5526 return ECC(A.second, B.second);
5527 });
5528
5529 // For a list of ordered instruction-vf pairs:
5530 // [(load, vf1), (load, vf2), (store, vf1)]
5531 // Group the instructions together to emit separate remarks for:
5532 // load (vf1, vf2)
5533 // store (vf1)
5534 auto Tail = ArrayRef<InstructionVFPair>(InvalidCosts);
5535 auto Subset = ArrayRef<InstructionVFPair>();
5536 do {
5537 if (Subset.empty())
5538 Subset = Tail.take_front(1);
5539
5540 Instruction *I = Subset.front().first;
5541
5542 // If the next instruction is different, or if there are no other pairs,
5543 // emit a remark for the collated subset. e.g.
5544 // [(load, vf1), (load, vf2))]
5545 // to emit:
5546 // remark: invalid costs for 'load' at VF=(vf, vf2)
5547 if (Subset == Tail || Tail[Subset.size()].first != I) {
5548 std::string OutString;
5549 raw_string_ostream OS(OutString);
5550 assert(!Subset.empty() && "Unexpected empty range")(static_cast <bool> (!Subset.empty() && "Unexpected empty range"
) ? void (0) : __assert_fail ("!Subset.empty() && \"Unexpected empty range\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5550, __extension__
__PRETTY_FUNCTION__))
;
5551 OS << "Instruction with invalid costs prevented vectorization at VF=(";
5552 for (auto &Pair : Subset)
5553 OS << (Pair.second == Subset.front().second ? "" : ", ")
5554 << Pair.second;
5555 OS << "):";
5556 if (auto *CI = dyn_cast<CallInst>(I))
5557 OS << " call to " << CI->getCalledFunction()->getName();
5558 else
5559 OS << " " << I->getOpcodeName();
5560 OS.flush();
5561 reportVectorizationInfo(OutString, "InvalidCost", ORE, TheLoop, I);
5562 Tail = Tail.drop_front(Subset.size());
5563 Subset = {};
5564 } else
5565 // Grow the subset by one element
5566 Subset = Tail.take_front(Subset.size() + 1);
5567 } while (!Tail.empty());
5568 }
5569
5570 if (!EnableCondStoresVectorization && NumPredStores) {
5571 reportVectorizationFailure("There are conditional stores.",
5572 "store that is conditionally executed prevents vectorization",
5573 "ConditionalStore", ORE, TheLoop);
5574 ChosenFactor = ScalarCost;
5575 }
5576
5577 LLVM_DEBUG(if (ForceVectorization && !ChosenFactor.Width.isScalar() &&do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { if (ForceVectorization && !ChosenFactor
.Width.isScalar() && ChosenFactor.Cost >= ScalarCost
.Cost) dbgs() << "LV: Vectorization seems to be not beneficial, "
<< "but was forced by a user.\n"; } } while (false)
5578 ChosenFactor.Cost >= ScalarCost.Cost) dbgs()do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { if (ForceVectorization && !ChosenFactor
.Width.isScalar() && ChosenFactor.Cost >= ScalarCost
.Cost) dbgs() << "LV: Vectorization seems to be not beneficial, "
<< "but was forced by a user.\n"; } } while (false)
5579 << "LV: Vectorization seems to be not beneficial, "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { if (ForceVectorization && !ChosenFactor
.Width.isScalar() && ChosenFactor.Cost >= ScalarCost
.Cost) dbgs() << "LV: Vectorization seems to be not beneficial, "
<< "but was forced by a user.\n"; } } while (false)
5580 << "but was forced by a user.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { if (ForceVectorization && !ChosenFactor
.Width.isScalar() && ChosenFactor.Cost >= ScalarCost
.Cost) dbgs() << "LV: Vectorization seems to be not beneficial, "
<< "but was forced by a user.\n"; } } while (false)
;
5581 LLVM_DEBUG(dbgs() << "LV: Selecting VF: " << ChosenFactor.Width << ".\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Selecting VF: " <<
ChosenFactor.Width << ".\n"; } } while (false)
;
5582 return ChosenFactor;
5583}
5584
5585bool LoopVectorizationCostModel::isCandidateForEpilogueVectorization(
5586 const Loop &L, ElementCount VF) const {
5587 // Cross iteration phis such as reductions need special handling and are
5588 // currently unsupported.
5589 if (any_of(L.getHeader()->phis(),
5590 [&](PHINode &Phi) { return Legal->isFirstOrderRecurrence(&Phi); }))
5591 return false;
5592
5593 // Phis with uses outside of the loop require special handling and are
5594 // currently unsupported.
5595 for (auto &Entry : Legal->getInductionVars()) {
5596 // Look for uses of the value of the induction at the last iteration.
5597 Value *PostInc = Entry.first->getIncomingValueForBlock(L.getLoopLatch());
5598 for (User *U : PostInc->users())
5599 if (!L.contains(cast<Instruction>(U)))
5600 return false;
5601 // Look for uses of penultimate value of the induction.
5602 for (User *U : Entry.first->users())
5603 if (!L.contains(cast<Instruction>(U)))
5604 return false;
5605 }
5606
5607 // Induction variables that are widened require special handling that is
5608 // currently not supported.
5609 if (any_of(Legal->getInductionVars(), [&](auto &Entry) {
5610 return !(this->isScalarAfterVectorization(Entry.first, VF) ||
5611 this->isProfitableToScalarize(Entry.first, VF));
5612 }))
5613 return false;
5614
5615 // Epilogue vectorization code has not been auditted to ensure it handles
5616 // non-latch exits properly. It may be fine, but it needs auditted and
5617 // tested.
5618 if (L.getExitingBlock() != L.getLoopLatch())
5619 return false;
5620
5621 return true;
5622}
5623
5624bool LoopVectorizationCostModel::isEpilogueVectorizationProfitable(
5625 const ElementCount VF) const {
5626 // FIXME: We need a much better cost-model to take different parameters such
5627 // as register pressure, code size increase and cost of extra branches into
5628 // account. For now we apply a very crude heuristic and only consider loops
5629 // with vectorization factors larger than a certain value.
5630 // We also consider epilogue vectorization unprofitable for targets that don't
5631 // consider interleaving beneficial (eg. MVE).
5632 if (TTI.getMaxInterleaveFactor(VF.getKnownMinValue()) <= 1)
5633 return false;
5634 // FIXME: We should consider changing the threshold for scalable
5635 // vectors to take VScaleForTuning into account.
5636 if (VF.getKnownMinValue() >= EpilogueVectorizationMinVF)
5637 return true;
5638 return false;
5639}
5640
5641VectorizationFactor
5642LoopVectorizationCostModel::selectEpilogueVectorizationFactor(
5643 const ElementCount MainLoopVF, const LoopVectorizationPlanner &LVP) {
5644 VectorizationFactor Result = VectorizationFactor::Disabled();
5645 if (!EnableEpilogueVectorization) {
5646 LLVM_DEBUG(dbgs() << "LEV: Epilogue vectorization is disabled.\n";)do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization is disabled.\n"
;; } } while (false)
;
5647 return Result;
5648 }
5649
5650 if (!isScalarEpilogueAllowed()) {
5651 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Unable to vectorize epilogue because no epilogue is "
"allowed.\n";; } } while (false)
5652 dbgs() << "LEV: Unable to vectorize epilogue because no epilogue is "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Unable to vectorize epilogue because no epilogue is "
"allowed.\n";; } } while (false)
5653 "allowed.\n";)do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Unable to vectorize epilogue because no epilogue is "
"allowed.\n";; } } while (false)
;
5654 return Result;
5655 }
5656
5657 // Not really a cost consideration, but check for unsupported cases here to
5658 // simplify the logic.
5659 if (!isCandidateForEpilogueVectorization(*TheLoop, MainLoopVF)) {
5660 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Unable to vectorize epilogue because the loop is "
"not a supported candidate.\n";; } } while (false)
5661 dbgs() << "LEV: Unable to vectorize epilogue because the loop is "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Unable to vectorize epilogue because the loop is "
"not a supported candidate.\n";; } } while (false)
5662 "not a supported candidate.\n";)do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Unable to vectorize epilogue because the loop is "
"not a supported candidate.\n";; } } while (false)
;
5663 return Result;
5664 }
5665
5666 if (EpilogueVectorizationForceVF > 1) {
5667 LLVM_DEBUG(dbgs() << "LEV: Epilogue vectorization factor is forced.\n";)do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization factor is forced.\n"
;; } } while (false)
;
5668 ElementCount ForcedEC = ElementCount::getFixed(EpilogueVectorizationForceVF);
5669 if (LVP.hasPlanWithVF(ForcedEC))
5670 return {ForcedEC, 0};
5671 else {
5672 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization forced factor is not viable.\n"
;; } } while (false)
5673 dbgs()do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization forced factor is not viable.\n"
;; } } while (false)
5674 << "LEV: Epilogue vectorization forced factor is not viable.\n";)do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization forced factor is not viable.\n"
;; } } while (false)
;
5675 return Result;
5676 }
5677 }
5678
5679 if (TheLoop->getHeader()->getParent()->hasOptSize() ||
5680 TheLoop->getHeader()->getParent()->hasMinSize()) {
5681 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization skipped due to opt for size.\n"
;; } } while (false)
5682 dbgs()do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization skipped due to opt for size.\n"
;; } } while (false)
5683 << "LEV: Epilogue vectorization skipped due to opt for size.\n";)do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization skipped due to opt for size.\n"
;; } } while (false)
;
5684 return Result;
5685 }
5686
5687 if (!isEpilogueVectorizationProfitable(MainLoopVF)) {
5688 LLVM_DEBUG(dbgs() << "LEV: Epilogue vectorization is not profitable for "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization is not profitable for "
"this loop\n"; } } while (false)
5689 "this loop\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Epilogue vectorization is not profitable for "
"this loop\n"; } } while (false)
;
5690 return Result;
5691 }
5692
5693 // If MainLoopVF = vscale x 2, and vscale is expected to be 4, then we know
5694 // the main loop handles 8 lanes per iteration. We could still benefit from
5695 // vectorizing the epilogue loop with VF=4.
5696 ElementCount EstimatedRuntimeVF = MainLoopVF;
5697 if (MainLoopVF.isScalable()) {
5698 EstimatedRuntimeVF = ElementCount::getFixed(MainLoopVF.getKnownMinValue());
5699 if (Optional<unsigned> VScale = getVScaleForTuning())
5700 EstimatedRuntimeVF *= VScale.getValue();
5701 }
5702
5703 for (auto &NextVF : ProfitableVFs)
5704 if (((!NextVF.Width.isScalable() && MainLoopVF.isScalable() &&
5705 ElementCount::isKnownLT(NextVF.Width, EstimatedRuntimeVF)) ||
5706 ElementCount::isKnownLT(NextVF.Width, MainLoopVF)) &&
5707 (Result.Width.isScalar() || isMoreProfitable(NextVF, Result)) &&
5708 LVP.hasPlanWithVF(NextVF.Width))
5709 Result = NextVF;
5710
5711 if (Result != VectorizationFactor::Disabled())
5712 LLVM_DEBUG(dbgs() << "LEV: Vectorizing epilogue loop with VF = "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Vectorizing epilogue loop with VF = "
<< Result.Width << "\n";; } } while (false)
5713 << Result.Width << "\n";)do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LEV: Vectorizing epilogue loop with VF = "
<< Result.Width << "\n";; } } while (false)
;
5714 return Result;
5715}
5716
5717std::pair<unsigned, unsigned>
5718LoopVectorizationCostModel::getSmallestAndWidestTypes() {
5719 unsigned MinWidth = -1U;
5720 unsigned MaxWidth = 8;
5721 const DataLayout &DL = TheFunction->getParent()->getDataLayout();
5722 // For in-loop reductions, no element types are added to ElementTypesInLoop
5723 // if there are no loads/stores in the loop. In this case, check through the
5724 // reduction variables to determine the maximum width.
5725 if (ElementTypesInLoop.empty() && !Legal->getReductionVars().empty()) {
5726 // Reset MaxWidth so that we can find the smallest type used by recurrences
5727 // in the loop.
5728 MaxWidth = -1U;
5729 for (auto &PhiDescriptorPair : Legal->getReductionVars()) {
5730 const RecurrenceDescriptor &RdxDesc = PhiDescriptorPair.second;
5731 // When finding the min width used by the recurrence we need to account
5732 // for casts on the input operands of the recurrence.
5733 MaxWidth = std::min<unsigned>(
5734 MaxWidth, std::min<unsigned>(
5735 RdxDesc.getMinWidthCastToRecurrenceTypeInBits(),
5736 RdxDesc.getRecurrenceType()->getScalarSizeInBits()));
5737 }
5738 } else {
5739 for (Type *T : ElementTypesInLoop) {
5740 MinWidth = std::min<unsigned>(
5741 MinWidth, DL.getTypeSizeInBits(T->getScalarType()).getFixedSize());
5742 MaxWidth = std::max<unsigned>(
5743 MaxWidth, DL.getTypeSizeInBits(T->getScalarType()).getFixedSize());
5744 }
5745 }
5746 return {MinWidth, MaxWidth};
5747}
5748
5749void LoopVectorizationCostModel::collectElementTypesForWidening() {
5750 ElementTypesInLoop.clear();
5751 // For each block.
5752 for (BasicBlock *BB : TheLoop->blocks()) {
5753 // For each instruction in the loop.
5754 for (Instruction &I : BB->instructionsWithoutDebug()) {
5755 Type *T = I.getType();
5756
5757 // Skip ignored values.
5758 if (ValuesToIgnore.count(&I))
5759 continue;
5760
5761 // Only examine Loads, Stores and PHINodes.
5762 if (!isa<LoadInst>(I) && !isa<StoreInst>(I) && !isa<PHINode>(I))
5763 continue;
5764
5765 // Examine PHI nodes that are reduction variables. Update the type to
5766 // account for the recurrence type.
5767 if (auto *PN = dyn_cast<PHINode>(&I)) {
5768 if (!Legal->isReductionVariable(PN))
5769 continue;
5770 const RecurrenceDescriptor &RdxDesc =
5771 Legal->getReductionVars().find(PN)->second;
5772 if (PreferInLoopReductions || useOrderedReductions(RdxDesc) ||
5773 TTI.preferInLoopReduction(RdxDesc.getOpcode(),
5774 RdxDesc.getRecurrenceType(),
5775 TargetTransformInfo::ReductionFlags()))
5776 continue;
5777 T = RdxDesc.getRecurrenceType();
5778 }
5779
5780 // Examine the stored values.
5781 if (auto *ST = dyn_cast<StoreInst>(&I))
5782 T = ST->getValueOperand()->getType();
5783
5784 assert(T->isSized() &&(static_cast <bool> (T->isSized() && "Expected the load/store/recurrence type to be sized"
) ? void (0) : __assert_fail ("T->isSized() && \"Expected the load/store/recurrence type to be sized\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5785, __extension__
__PRETTY_FUNCTION__))
5785 "Expected the load/store/recurrence type to be sized")(static_cast <bool> (T->isSized() && "Expected the load/store/recurrence type to be sized"
) ? void (0) : __assert_fail ("T->isSized() && \"Expected the load/store/recurrence type to be sized\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5785, __extension__
__PRETTY_FUNCTION__))
;
5786
5787 ElementTypesInLoop.insert(T);
5788 }
5789 }
5790}
5791
5792unsigned LoopVectorizationCostModel::selectInterleaveCount(ElementCount VF,
5793 unsigned LoopCost) {
5794 // -- The interleave heuristics --
5795 // We interleave the loop in order to expose ILP and reduce the loop overhead.
5796 // There are many micro-architectural considerations that we can't predict
5797 // at this level. For example, frontend pressure (on decode or fetch) due to
5798 // code size, or the number and capabilities of the execution ports.
5799 //
5800 // We use the following heuristics to select the interleave count:
5801 // 1. If the code has reductions, then we interleave to break the cross
5802 // iteration dependency.
5803 // 2. If the loop is really small, then we interleave to reduce the loop
5804 // overhead.
5805 // 3. We don't interleave if we think that we will spill registers to memory
5806 // due to the increased register pressure.
5807
5808 if (!isScalarEpilogueAllowed())
5809 return 1;
5810
5811 // We used the distance for the interleave count.
5812 if (Legal->getMaxSafeDepDistBytes() != -1U)
5813 return 1;
5814
5815 auto BestKnownTC = getSmallBestKnownTC(*PSE.getSE(), TheLoop);
5816 const bool HasReductions = !Legal->getReductionVars().empty();
5817 // Do not interleave loops with a relatively small known or estimated trip
5818 // count. But we will interleave when InterleaveSmallLoopScalarReduction is
5819 // enabled, and the code has scalar reductions(HasReductions && VF = 1),
5820 // because with the above conditions interleaving can expose ILP and break
5821 // cross iteration dependences for reductions.
5822 if (BestKnownTC && (*BestKnownTC < TinyTripCountInterleaveThreshold) &&
5823 !(InterleaveSmallLoopScalarReduction && HasReductions && VF.isScalar()))
5824 return 1;
5825
5826 RegisterUsage R = calculateRegisterUsage({VF})[0];
5827 // We divide by these constants so assume that we have at least one
5828 // instruction that uses at least one register.
5829 for (auto& pair : R.MaxLocalUsers) {
5830 pair.second = std::max(pair.second, 1U);
5831 }
5832
5833 // We calculate the interleave count using the following formula.
5834 // Subtract the number of loop invariants from the number of available
5835 // registers. These registers are used by all of the interleaved instances.
5836 // Next, divide the remaining registers by the number of registers that is
5837 // required by the loop, in order to estimate how many parallel instances
5838 // fit without causing spills. All of this is rounded down if necessary to be
5839 // a power of two. We want power of two interleave count to simplify any
5840 // addressing operations or alignment considerations.
5841 // We also want power of two interleave counts to ensure that the induction
5842 // variable of the vector loop wraps to zero, when tail is folded by masking;
5843 // this currently happens when OptForSize, in which case IC is set to 1 above.
5844 unsigned IC = UINT_MAX(2147483647 *2U +1U);
5845
5846 for (auto& pair : R.MaxLocalUsers) {
5847 unsigned TargetNumRegisters = TTI.getNumberOfRegisters(pair.first);
5848 LLVM_DEBUG(dbgs() << "LV: The target has " << TargetNumRegistersdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The target has " <<
TargetNumRegisters << " registers of " << TTI.getRegisterClassName
(pair.first) << " register class\n"; } } while (false)
5849 << " registers of "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The target has " <<
TargetNumRegisters << " registers of " << TTI.getRegisterClassName
(pair.first) << " register class\n"; } } while (false)
5850 << TTI.getRegisterClassName(pair.first) << " register class\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: The target has " <<
TargetNumRegisters << " registers of " << TTI.getRegisterClassName
(pair.first) << " register class\n"; } } while (false)
;
5851 if (VF.isScalar()) {
5852 if (ForceTargetNumScalarRegs.getNumOccurrences() > 0)
5853 TargetNumRegisters = ForceTargetNumScalarRegs;
5854 } else {
5855 if (ForceTargetNumVectorRegs.getNumOccurrences() > 0)
5856 TargetNumRegisters = ForceTargetNumVectorRegs;
5857 }
5858 unsigned MaxLocalUsers = pair.second;
5859 unsigned LoopInvariantRegs = 0;
5860 if (R.LoopInvariantRegs.find(pair.first) != R.LoopInvariantRegs.end())
5861 LoopInvariantRegs = R.LoopInvariantRegs[pair.first];
5862
5863 unsigned TmpIC = PowerOf2Floor((TargetNumRegisters - LoopInvariantRegs) / MaxLocalUsers);
5864 // Don't count the induction variable as interleaved.
5865 if (EnableIndVarRegisterHeur) {
5866 TmpIC =
5867 PowerOf2Floor((TargetNumRegisters - LoopInvariantRegs - 1) /
5868 std::max(1U, (MaxLocalUsers - 1)));
5869 }
5870
5871 IC = std::min(IC, TmpIC);
5872 }
5873
5874 // Clamp the interleave ranges to reasonable counts.
5875 unsigned MaxInterleaveCount =
5876 TTI.getMaxInterleaveFactor(VF.getKnownMinValue());
5877
5878 // Check if the user has overridden the max.
5879 if (VF.isScalar()) {
5880 if (ForceTargetMaxScalarInterleaveFactor.getNumOccurrences() > 0)
5881 MaxInterleaveCount = ForceTargetMaxScalarInterleaveFactor;
5882 } else {
5883 if (ForceTargetMaxVectorInterleaveFactor.getNumOccurrences() > 0)
5884 MaxInterleaveCount = ForceTargetMaxVectorInterleaveFactor;
5885 }
5886
5887 // If trip count is known or estimated compile time constant, limit the
5888 // interleave count to be less than the trip count divided by VF, provided it
5889 // is at least 1.
5890 //
5891 // For scalable vectors we can't know if interleaving is beneficial. It may
5892 // not be beneficial for small loops if none of the lanes in the second vector
5893 // iterations is enabled. However, for larger loops, there is likely to be a
5894 // similar benefit as for fixed-width vectors. For now, we choose to leave
5895 // the InterleaveCount as if vscale is '1', although if some information about
5896 // the vector is known (e.g. min vector size), we can make a better decision.
5897 if (BestKnownTC) {
5898 MaxInterleaveCount =
5899 std::min(*BestKnownTC / VF.getKnownMinValue(), MaxInterleaveCount);
5900 // Make sure MaxInterleaveCount is greater than 0.
5901 MaxInterleaveCount = std::max(1u, MaxInterleaveCount);
5902 }
5903
5904 assert(MaxInterleaveCount > 0 &&(static_cast <bool> (MaxInterleaveCount > 0 &&
"Maximum interleave count must be greater than 0") ? void (0
) : __assert_fail ("MaxInterleaveCount > 0 && \"Maximum interleave count must be greater than 0\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5905, __extension__
__PRETTY_FUNCTION__))
5905 "Maximum interleave count must be greater than 0")(static_cast <bool> (MaxInterleaveCount > 0 &&
"Maximum interleave count must be greater than 0") ? void (0
) : __assert_fail ("MaxInterleaveCount > 0 && \"Maximum interleave count must be greater than 0\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5905, __extension__
__PRETTY_FUNCTION__))
;
5906
5907 // Clamp the calculated IC to be between the 1 and the max interleave count
5908 // that the target and trip count allows.
5909 if (IC > MaxInterleaveCount)
5910 IC = MaxInterleaveCount;
5911 else
5912 // Make sure IC is greater than 0.
5913 IC = std::max(1u, IC);
5914
5915 assert(IC > 0 && "Interleave count must be greater than 0.")(static_cast <bool> (IC > 0 && "Interleave count must be greater than 0."
) ? void (0) : __assert_fail ("IC > 0 && \"Interleave count must be greater than 0.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5915, __extension__
__PRETTY_FUNCTION__))
;
5916
5917 // If we did not calculate the cost for VF (because the user selected the VF)
5918 // then we calculate the cost of VF here.
5919 if (LoopCost == 0) {
5920 InstructionCost C = expectedCost(VF).first;
5921 assert(C.isValid() && "Expected to have chosen a VF with valid cost")(static_cast <bool> (C.isValid() && "Expected to have chosen a VF with valid cost"
) ? void (0) : __assert_fail ("C.isValid() && \"Expected to have chosen a VF with valid cost\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5921, __extension__
__PRETTY_FUNCTION__))
;
5922 LoopCost = *C.getValue();
5923 }
5924
5925 assert(LoopCost && "Non-zero loop cost expected")(static_cast <bool> (LoopCost && "Non-zero loop cost expected"
) ? void (0) : __assert_fail ("LoopCost && \"Non-zero loop cost expected\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 5925, __extension__
__PRETTY_FUNCTION__))
;
5926
5927 // Interleave if we vectorized this loop and there is a reduction that could
5928 // benefit from interleaving.
5929 if (VF.isVector() && HasReductions) {
5930 LLVM_DEBUG(dbgs() << "LV: Interleaving because of reductions.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving because of reductions.\n"
; } } while (false)
;
5931 return IC;
5932 }
5933
5934 // For any scalar loop that either requires runtime checks or predication we
5935 // are better off leaving this to the unroller. Note that if we've already
5936 // vectorized the loop we will have done the runtime check and so interleaving
5937 // won't require further checks.
5938 bool ScalarInterleavingRequiresPredication =
5939 (VF.isScalar() && any_of(TheLoop->blocks(), [this](BasicBlock *BB) {
5940 return Legal->blockNeedsPredication(BB);
5941 }));
5942 bool ScalarInterleavingRequiresRuntimePointerCheck =
5943 (VF.isScalar() && Legal->getRuntimePointerChecking()->Need);
5944
5945 // We want to interleave small loops in order to reduce the loop overhead and
5946 // potentially expose ILP opportunities.
5947 LLVM_DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n'do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop cost is " <<
LoopCost << '\n' << "LV: IC is " << IC <<
'\n' << "LV: VF is " << VF << '\n'; } } while
(false)
5948 << "LV: IC is " << IC << '\n'do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop cost is " <<
LoopCost << '\n' << "LV: IC is " << IC <<
'\n' << "LV: VF is " << VF << '\n'; } } while
(false)
5949 << "LV: VF is " << VF << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop cost is " <<
LoopCost << '\n' << "LV: IC is " << IC <<
'\n' << "LV: VF is " << VF << '\n'; } } while
(false)
;
5950 const bool AggressivelyInterleaveReductions =
5951 TTI.enableAggressiveInterleaving(HasReductions);
5952 if (!ScalarInterleavingRequiresRuntimePointerCheck &&
5953 !ScalarInterleavingRequiresPredication && LoopCost < SmallLoopCost) {
5954 // We assume that the cost overhead is 1 and we use the cost model
5955 // to estimate the cost of the loop and interleave until the cost of the
5956 // loop overhead is about 5% of the cost of the loop.
5957 unsigned SmallIC =
5958 std::min(IC, (unsigned)PowerOf2Floor(SmallLoopCost / LoopCost));
5959
5960 // Interleave until store/load ports (estimated by max interleave count) are
5961 // saturated.
5962 unsigned NumStores = Legal->getNumStores();
5963 unsigned NumLoads = Legal->getNumLoads();
5964 unsigned StoresIC = IC / (NumStores ? NumStores : 1);
5965 unsigned LoadsIC = IC / (NumLoads ? NumLoads : 1);
5966
5967 // There is little point in interleaving for reductions containing selects
5968 // and compares when VF=1 since it may just create more overhead than it's
5969 // worth for loops with small trip counts. This is because we still have to
5970 // do the final reduction after the loop.
5971 bool HasSelectCmpReductions =
5972 HasReductions &&
5973 any_of(Legal->getReductionVars(), [&](auto &Reduction) -> bool {
5974 const RecurrenceDescriptor &RdxDesc = Reduction.second;
5975 return RecurrenceDescriptor::isSelectCmpRecurrenceKind(
5976 RdxDesc.getRecurrenceKind());
5977 });
5978 if (HasSelectCmpReductions) {
5979 LLVM_DEBUG(dbgs() << "LV: Not interleaving select-cmp reductions.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not interleaving select-cmp reductions.\n"
; } } while (false)
;
5980 return 1;
5981 }
5982
5983 // If we have a scalar reduction (vector reductions are already dealt with
5984 // by this point), we can increase the critical path length if the loop
5985 // we're interleaving is inside another loop. For tree-wise reductions
5986 // set the limit to 2, and for ordered reductions it's best to disable
5987 // interleaving entirely.
5988 if (HasReductions && TheLoop->getLoopDepth() > 1) {
5989 bool HasOrderedReductions =
5990 any_of(Legal->getReductionVars(), [&](auto &Reduction) -> bool {
5991 const RecurrenceDescriptor &RdxDesc = Reduction.second;
5992 return RdxDesc.isOrdered();
5993 });
5994 if (HasOrderedReductions) {
5995 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not interleaving scalar ordered reductions.\n"
; } } while (false)
5996 dbgs() << "LV: Not interleaving scalar ordered reductions.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not interleaving scalar ordered reductions.\n"
; } } while (false)
;
5997 return 1;
5998 }
5999
6000 unsigned F = static_cast<unsigned>(MaxNestedScalarReductionIC);
6001 SmallIC = std::min(SmallIC, F);
6002 StoresIC = std::min(StoresIC, F);
6003 LoadsIC = std::min(LoadsIC, F);
6004 }
6005
6006 if (EnableLoadStoreRuntimeInterleave &&
6007 std::max(StoresIC, LoadsIC) > SmallIC) {
6008 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving to saturate store or load ports.\n"
; } } while (false)
6009 dbgs() << "LV: Interleaving to saturate store or load ports.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving to saturate store or load ports.\n"
; } } while (false)
;
6010 return std::max(StoresIC, LoadsIC);
6011 }
6012
6013 // If there are scalar reductions and TTI has enabled aggressive
6014 // interleaving for reductions, we will interleave to expose ILP.
6015 if (InterleaveSmallLoopScalarReduction && VF.isScalar() &&
6016 AggressivelyInterleaveReductions) {
6017 LLVM_DEBUG(dbgs() << "LV: Interleaving to expose ILP.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving to expose ILP.\n"
; } } while (false)
;
6018 // Interleave no less than SmallIC but not as aggressive as the normal IC
6019 // to satisfy the rare situation when resources are too limited.
6020 return std::max(IC / 2, SmallIC);
6021 } else {
6022 LLVM_DEBUG(dbgs() << "LV: Interleaving to reduce branch cost.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving to reduce branch cost.\n"
; } } while (false)
;
6023 return SmallIC;
6024 }
6025 }
6026
6027 // Interleave if this is a large loop (small loops are already dealt with by
6028 // this point) that could benefit from interleaving.
6029 if (AggressivelyInterleaveReductions) {
6030 LLVM_DEBUG(dbgs() << "LV: Interleaving to expose ILP.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving to expose ILP.\n"
; } } while (false)
;
6031 return IC;
6032 }
6033
6034 LLVM_DEBUG(dbgs() << "LV: Not Interleaving.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not Interleaving.\n"
; } } while (false)
;
6035 return 1;
6036}
6037
6038SmallVector<LoopVectorizationCostModel::RegisterUsage, 8>
6039LoopVectorizationCostModel::calculateRegisterUsage(ArrayRef<ElementCount> VFs) {
6040 // This function calculates the register usage by measuring the highest number
6041 // of values that are alive at a single location. Obviously, this is a very
6042 // rough estimation. We scan the loop in a topological order in order and
6043 // assign a number to each instruction. We use RPO to ensure that defs are
6044 // met before their users. We assume that each instruction that has in-loop
6045 // users starts an interval. We record every time that an in-loop value is
6046 // used, so we have a list of the first and last occurrences of each
6047 // instruction. Next, we transpose this data structure into a multi map that
6048 // holds the list of intervals that *end* at a specific location. This multi
6049 // map allows us to perform a linear search. We scan the instructions linearly
6050 // and record each time that a new interval starts, by placing it in a set.
6051 // If we find this value in the multi-map then we remove it from the set.
6052 // The max register usage is the maximum size of the set.
6053 // We also search for instructions that are defined outside the loop, but are
6054 // used inside the loop. We need this number separately from the max-interval
6055 // usage number because when we unroll, loop-invariant values do not take
6056 // more register.
6057 LoopBlocksDFS DFS(TheLoop);
6058 DFS.perform(LI);
6059
6060 RegisterUsage RU;
6061
6062 // Each 'key' in the map opens a new interval. The values
6063 // of the map are the index of the 'last seen' usage of the
6064 // instruction that is the key.
6065 using IntervalMap = DenseMap<Instruction *, unsigned>;
6066
6067 // Maps instruction to its index.
6068 SmallVector<Instruction *, 64> IdxToInstr;
6069 // Marks the end of each interval.
6070 IntervalMap EndPoint;
6071 // Saves the list of instruction indices that are used in the loop.
6072 SmallPtrSet<Instruction *, 8> Ends;
6073 // Saves the list of values that are used in the loop but are
6074 // defined outside the loop, such as arguments and constants.
6075 SmallPtrSet<Value *, 8> LoopInvariants;
6076
6077 for (BasicBlock *BB : make_range(DFS.beginRPO(), DFS.endRPO())) {
6078 for (Instruction &I : BB->instructionsWithoutDebug()) {
6079 IdxToInstr.push_back(&I);
6080
6081 // Save the end location of each USE.
6082 for (Value *U : I.operands()) {
6083 auto *Instr = dyn_cast<Instruction>(U);
6084
6085 // Ignore non-instruction values such as arguments, constants, etc.
6086 if (!Instr)
6087 continue;
6088
6089 // If this instruction is outside the loop then record it and continue.
6090 if (!TheLoop->contains(Instr)) {
6091 LoopInvariants.insert(Instr);
6092 continue;
6093 }
6094
6095 // Overwrite previous end points.
6096 EndPoint[Instr] = IdxToInstr.size();
6097 Ends.insert(Instr);
6098 }
6099 }
6100 }
6101
6102 // Saves the list of intervals that end with the index in 'key'.
6103 using InstrList = SmallVector<Instruction *, 2>;
6104 DenseMap<unsigned, InstrList> TransposeEnds;
6105
6106 // Transpose the EndPoints to a list of values that end at each index.
6107 for (auto &Interval : EndPoint)
6108 TransposeEnds[Interval.second].push_back(Interval.first);
6109
6110 SmallPtrSet<Instruction *, 8> OpenIntervals;
6111 SmallVector<RegisterUsage, 8> RUs(VFs.size());
6112 SmallVector<SmallMapVector<unsigned, unsigned, 4>, 8> MaxUsages(VFs.size());
6113
6114 LLVM_DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV(REG): Calculating max register usage:\n"
; } } while (false)
;
6115
6116 // A lambda that gets the register usage for the given type and VF.
6117 const auto &TTICapture = TTI;
6118 auto GetRegUsage = [&TTICapture](Type *Ty, ElementCount VF) -> unsigned {
6119 if (Ty->isTokenTy() || !VectorType::isValidElementType(Ty))
6120 return 0;
6121 InstructionCost::CostType RegUsage =
6122 *TTICapture.getRegUsageForType(VectorType::get(Ty, VF)).getValue();
6123 assert(RegUsage >= 0 && RegUsage <= std::numeric_limits<unsigned>::max() &&(static_cast <bool> (RegUsage >= 0 && RegUsage
<= std::numeric_limits<unsigned>::max() && "Nonsensical values for register usage."
) ? void (0) : __assert_fail ("RegUsage >= 0 && RegUsage <= std::numeric_limits<unsigned>::max() && \"Nonsensical values for register usage.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6124, __extension__
__PRETTY_FUNCTION__))
6124 "Nonsensical values for register usage.")(static_cast <bool> (RegUsage >= 0 && RegUsage
<= std::numeric_limits<unsigned>::max() && "Nonsensical values for register usage."
) ? void (0) : __assert_fail ("RegUsage >= 0 && RegUsage <= std::numeric_limits<unsigned>::max() && \"Nonsensical values for register usage.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6124, __extension__
__PRETTY_FUNCTION__))
;
6125 return RegUsage;
6126 };
6127
6128 for (unsigned int i = 0, s = IdxToInstr.size(); i < s; ++i) {
6129 Instruction *I = IdxToInstr[i];
6130
6131 // Remove all of the instructions that end at this location.
6132 InstrList &List = TransposeEnds[i];
6133 for (Instruction *ToRemove : List)
6134 OpenIntervals.erase(ToRemove);
6135
6136 // Ignore instructions that are never used within the loop.
6137 if (!Ends.count(I))
6138 continue;
6139
6140 // Skip ignored values.
6141 if (ValuesToIgnore.count(I))
6142 continue;
6143
6144 // For each VF find the maximum usage of registers.
6145 for (unsigned j = 0, e = VFs.size(); j < e; ++j) {
6146 // Count the number of live intervals.
6147 SmallMapVector<unsigned, unsigned, 4> RegUsage;
6148
6149 if (VFs[j].isScalar()) {
6150 for (auto Inst : OpenIntervals) {
6151 unsigned ClassID = TTI.getRegisterClassForType(false, Inst->getType());
6152 if (RegUsage.find(ClassID) == RegUsage.end())
6153 RegUsage[ClassID] = 1;
6154 else
6155 RegUsage[ClassID] += 1;
6156 }
6157 } else {
6158 collectUniformsAndScalars(VFs[j]);
6159 for (auto Inst : OpenIntervals) {
6160 // Skip ignored values for VF > 1.
6161 if (VecValuesToIgnore.count(Inst))
6162 continue;
6163 if (isScalarAfterVectorization(Inst, VFs[j])) {
6164 unsigned ClassID = TTI.getRegisterClassForType(false, Inst->getType());
6165 if (RegUsage.find(ClassID) == RegUsage.end())
6166 RegUsage[ClassID] = 1;
6167 else
6168 RegUsage[ClassID] += 1;
6169 } else {
6170 unsigned ClassID = TTI.getRegisterClassForType(true, Inst->getType());
6171 if (RegUsage.find(ClassID) == RegUsage.end())
6172 RegUsage[ClassID] = GetRegUsage(Inst->getType(), VFs[j]);
6173 else
6174 RegUsage[ClassID] += GetRegUsage(Inst->getType(), VFs[j]);
6175 }
6176 }
6177 }
6178
6179 for (auto& pair : RegUsage) {
6180 if (MaxUsages[j].find(pair.first) != MaxUsages[j].end())
6181 MaxUsages[j][pair.first] = std::max(MaxUsages[j][pair.first], pair.second);
6182 else
6183 MaxUsages[j][pair.first] = pair.second;
6184 }
6185 }
6186
6187 LLVM_DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV(REG): At #" <<
i << " Interval # " << OpenIntervals.size() <<
'\n'; } } while (false)
6188 << OpenIntervals.size() << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV(REG): At #" <<
i << " Interval # " << OpenIntervals.size() <<
'\n'; } } while (false)
;
6189
6190 // Add the current instruction to the list of open intervals.
6191 OpenIntervals.insert(I);
6192 }
6193
6194 for (unsigned i = 0, e = VFs.size(); i < e; ++i) {
6195 SmallMapVector<unsigned, unsigned, 4> Invariant;
6196
6197 for (auto Inst : LoopInvariants) {
6198 unsigned Usage =
6199 VFs[i].isScalar() ? 1 : GetRegUsage(Inst->getType(), VFs[i]);
6200 unsigned ClassID =
6201 TTI.getRegisterClassForType(VFs[i].isVector(), Inst->getType());
6202 if (Invariant.find(ClassID) == Invariant.end())
6203 Invariant[ClassID] = Usage;
6204 else
6205 Invariant[ClassID] += Usage;
6206 }
6207
6208 LLVM_DEBUG({do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6209 dbgs() << "LV(REG): VF = " << VFs[i] << '\n';do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6210 dbgs() << "LV(REG): Found max usage: " << MaxUsages[i].size()do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6211 << " item\n";do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6212 for (const auto &pair : MaxUsages[i]) {do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6213 dbgs() << "LV(REG): RegisterClass: "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6214 << TTI.getRegisterClassName(pair.first) << ", " << pair.seconddo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6215 << " registers\n";do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6216 }do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6217 dbgs() << "LV(REG): Found invariant usage: " << Invariant.size()do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6218 << " item\n";do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6219 for (const auto &pair : Invariant) {do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6220 dbgs() << "LV(REG): RegisterClass: "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6221 << TTI.getRegisterClassName(pair.first) << ", " << pair.seconddo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6222 << " registers\n";do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6223 }do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
6224 })do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "LV(REG): VF = " <<
VFs[i] << '\n'; dbgs() << "LV(REG): Found max usage: "
<< MaxUsages[i].size() << " item\n"; for (const auto
&pair : MaxUsages[i]) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } dbgs() << "LV(REG): Found invariant usage: "
<< Invariant.size() << " item\n"; for (const auto
&pair : Invariant) { dbgs() << "LV(REG): RegisterClass: "
<< TTI.getRegisterClassName(pair.first) << ", " <<
pair.second << " registers\n"; } }; } } while (false)
;
6225
6226 RU.LoopInvariantRegs = Invariant;
6227 RU.MaxLocalUsers = MaxUsages[i];
6228 RUs[i] = RU;
6229 }
6230
6231 return RUs;
6232}
6233
6234bool LoopVectorizationCostModel::useEmulatedMaskMemRefHack(Instruction *I,
6235 ElementCount VF) {
6236 // TODO: Cost model for emulated masked load/store is completely
6237 // broken. This hack guides the cost model to use an artificially
6238 // high enough value to practically disable vectorization with such
6239 // operations, except where previously deployed legality hack allowed
6240 // using very low cost values. This is to avoid regressions coming simply
6241 // from moving "masked load/store" check from legality to cost model.
6242 // Masked Load/Gather emulation was previously never allowed.
6243 // Limited number of Masked Store/Scatter emulation was allowed.
6244 assert(isPredicatedInst(I, VF) && "Expecting a scalar emulated instruction")(static_cast <bool> (isPredicatedInst(I, VF) &&
"Expecting a scalar emulated instruction") ? void (0) : __assert_fail
("isPredicatedInst(I, VF) && \"Expecting a scalar emulated instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6244, __extension__
__PRETTY_FUNCTION__))
;
6245 return isa<LoadInst>(I) ||
6246 (isa<StoreInst>(I) &&
6247 NumPredStores > NumberOfStoresToPredicate);
6248}
6249
6250void LoopVectorizationCostModel::collectInstsToScalarize(ElementCount VF) {
6251 // If we aren't vectorizing the loop, or if we've already collected the
6252 // instructions to scalarize, there's nothing to do. Collection may already
6253 // have occurred if we have a user-selected VF and are now computing the
6254 // expected cost for interleaving.
6255 if (VF.isScalar() || VF.isZero() ||
6256 InstsToScalarize.find(VF) != InstsToScalarize.end())
6257 return;
6258
6259 // Initialize a mapping for VF in InstsToScalalarize. If we find that it's
6260 // not profitable to scalarize any instructions, the presence of VF in the
6261 // map will indicate that we've analyzed it already.
6262 ScalarCostsTy &ScalarCostsVF = InstsToScalarize[VF];
6263
6264 // Find all the instructions that are scalar with predication in the loop and
6265 // determine if it would be better to not if-convert the blocks they are in.
6266 // If so, we also record the instructions to scalarize.
6267 for (BasicBlock *BB : TheLoop->blocks()) {
6268 if (!blockNeedsPredicationForAnyReason(BB))
6269 continue;
6270 for (Instruction &I : *BB)
6271 if (isScalarWithPredication(&I, VF)) {
6272 ScalarCostsTy ScalarCosts;
6273 // Do not apply discount if scalable, because that would lead to
6274 // invalid scalarization costs.
6275 // Do not apply discount logic if hacked cost is needed
6276 // for emulated masked memrefs.
6277 if (!VF.isScalable() && !useEmulatedMaskMemRefHack(&I, VF) &&
6278 computePredInstDiscount(&I, ScalarCosts, VF) >= 0)
6279 ScalarCostsVF.insert(ScalarCosts.begin(), ScalarCosts.end());
6280 // Remember that BB will remain after vectorization.
6281 PredicatedBBsAfterVectorization.insert(BB);
6282 }
6283 }
6284}
6285
6286int LoopVectorizationCostModel::computePredInstDiscount(
6287 Instruction *PredInst, ScalarCostsTy &ScalarCosts, ElementCount VF) {
6288 assert(!isUniformAfterVectorization(PredInst, VF) &&(static_cast <bool> (!isUniformAfterVectorization(PredInst
, VF) && "Instruction marked uniform-after-vectorization will be predicated"
) ? void (0) : __assert_fail ("!isUniformAfterVectorization(PredInst, VF) && \"Instruction marked uniform-after-vectorization will be predicated\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6289, __extension__
__PRETTY_FUNCTION__))
6289 "Instruction marked uniform-after-vectorization will be predicated")(static_cast <bool> (!isUniformAfterVectorization(PredInst
, VF) && "Instruction marked uniform-after-vectorization will be predicated"
) ? void (0) : __assert_fail ("!isUniformAfterVectorization(PredInst, VF) && \"Instruction marked uniform-after-vectorization will be predicated\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6289, __extension__
__PRETTY_FUNCTION__))
;
6290
6291 // Initialize the discount to zero, meaning that the scalar version and the
6292 // vector version cost the same.
6293 InstructionCost Discount = 0;
6294
6295 // Holds instructions to analyze. The instructions we visit are mapped in
6296 // ScalarCosts. Those instructions are the ones that would be scalarized if
6297 // we find that the scalar version costs less.
6298 SmallVector<Instruction *, 8> Worklist;
6299
6300 // Returns true if the given instruction can be scalarized.
6301 auto canBeScalarized = [&](Instruction *I) -> bool {
6302 // We only attempt to scalarize instructions forming a single-use chain
6303 // from the original predicated block that would otherwise be vectorized.
6304 // Although not strictly necessary, we give up on instructions we know will
6305 // already be scalar to avoid traversing chains that are unlikely to be
6306 // beneficial.
6307 if (!I->hasOneUse() || PredInst->getParent() != I->getParent() ||
6308 isScalarAfterVectorization(I, VF))
6309 return false;
6310
6311 // If the instruction is scalar with predication, it will be analyzed
6312 // separately. We ignore it within the context of PredInst.
6313 if (isScalarWithPredication(I, VF))
6314 return false;
6315
6316 // If any of the instruction's operands are uniform after vectorization,
6317 // the instruction cannot be scalarized. This prevents, for example, a
6318 // masked load from being scalarized.
6319 //
6320 // We assume we will only emit a value for lane zero of an instruction
6321 // marked uniform after vectorization, rather than VF identical values.
6322 // Thus, if we scalarize an instruction that uses a uniform, we would
6323 // create uses of values corresponding to the lanes we aren't emitting code
6324 // for. This behavior can be changed by allowing getScalarValue to clone
6325 // the lane zero values for uniforms rather than asserting.
6326 for (Use &U : I->operands())
6327 if (auto *J = dyn_cast<Instruction>(U.get()))
6328 if (isUniformAfterVectorization(J, VF))
6329 return false;
6330
6331 // Otherwise, we can scalarize the instruction.
6332 return true;
6333 };
6334
6335 // Compute the expected cost discount from scalarizing the entire expression
6336 // feeding the predicated instruction. We currently only consider expressions
6337 // that are single-use instruction chains.
6338 Worklist.push_back(PredInst);
6339 while (!Worklist.empty()) {
6340 Instruction *I = Worklist.pop_back_val();
6341
6342 // If we've already analyzed the instruction, there's nothing to do.
6343 if (ScalarCosts.find(I) != ScalarCosts.end())
6344 continue;
6345
6346 // Compute the cost of the vector instruction. Note that this cost already
6347 // includes the scalarization overhead of the predicated instruction.
6348 InstructionCost VectorCost = getInstructionCost(I, VF).first;
6349
6350 // Compute the cost of the scalarized instruction. This cost is the cost of
6351 // the instruction as if it wasn't if-converted and instead remained in the
6352 // predicated block. We will scale this cost by block probability after
6353 // computing the scalarization overhead.
6354 InstructionCost ScalarCost =
6355 VF.getFixedValue() *
6356 getInstructionCost(I, ElementCount::getFixed(1)).first;
6357
6358 // Compute the scalarization overhead of needed insertelement instructions
6359 // and phi nodes.
6360 if (isScalarWithPredication(I, VF) && !I->getType()->isVoidTy()) {
6361 ScalarCost += TTI.getScalarizationOverhead(
6362 cast<VectorType>(ToVectorTy(I->getType(), VF)),
6363 APInt::getAllOnes(VF.getFixedValue()), true, false);
6364 ScalarCost +=
6365 VF.getFixedValue() *
6366 TTI.getCFInstrCost(Instruction::PHI, TTI::TCK_RecipThroughput);
6367 }
6368
6369 // Compute the scalarization overhead of needed extractelement
6370 // instructions. For each of the instruction's operands, if the operand can
6371 // be scalarized, add it to the worklist; otherwise, account for the
6372 // overhead.
6373 for (Use &U : I->operands())
6374 if (auto *J = dyn_cast<Instruction>(U.get())) {
6375 assert(VectorType::isValidElementType(J->getType()) &&(static_cast <bool> (VectorType::isValidElementType(J->
getType()) && "Instruction has non-scalar type") ? void
(0) : __assert_fail ("VectorType::isValidElementType(J->getType()) && \"Instruction has non-scalar type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6376, __extension__
__PRETTY_FUNCTION__))
6376 "Instruction has non-scalar type")(static_cast <bool> (VectorType::isValidElementType(J->
getType()) && "Instruction has non-scalar type") ? void
(0) : __assert_fail ("VectorType::isValidElementType(J->getType()) && \"Instruction has non-scalar type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6376, __extension__
__PRETTY_FUNCTION__))
;
6377 if (canBeScalarized(J))
6378 Worklist.push_back(J);
6379 else if (needsExtract(J, VF)) {
6380 ScalarCost += TTI.getScalarizationOverhead(
6381 cast<VectorType>(ToVectorTy(J->getType(), VF)),
6382 APInt::getAllOnes(VF.getFixedValue()), false, true);
6383 }
6384 }
6385
6386 // Scale the total scalar cost by block probability.
6387 ScalarCost /= getReciprocalPredBlockProb();
6388
6389 // Compute the discount. A non-negative discount means the vector version
6390 // of the instruction costs more, and scalarizing would be beneficial.
6391 Discount += VectorCost - ScalarCost;
6392 ScalarCosts[I] = ScalarCost;
6393 }
6394
6395 return *Discount.getValue();
6396}
6397
6398LoopVectorizationCostModel::VectorizationCostTy
6399LoopVectorizationCostModel::expectedCost(
6400 ElementCount VF, SmallVectorImpl<InstructionVFPair> *Invalid) {
6401 VectorizationCostTy Cost;
6402
6403 // For each block.
6404 for (BasicBlock *BB : TheLoop->blocks()) {
6405 VectorizationCostTy BlockCost;
6406
6407 // For each instruction in the old loop.
6408 for (Instruction &I : BB->instructionsWithoutDebug()) {
6409 // Skip ignored values.
6410 if (ValuesToIgnore.count(&I) ||
6411 (VF.isVector() && VecValuesToIgnore.count(&I)))
6412 continue;
6413
6414 VectorizationCostTy C = getInstructionCost(&I, VF);
6415
6416 // Check if we should override the cost.
6417 if (C.first.isValid() &&
6418 ForceTargetInstructionCost.getNumOccurrences() > 0)
6419 C.first = InstructionCost(ForceTargetInstructionCost);
6420
6421 // Keep a list of instructions with invalid costs.
6422 if (Invalid && !C.first.isValid())
6423 Invalid->emplace_back(&I, VF);
6424
6425 BlockCost.first += C.first;
6426 BlockCost.second |= C.second;
6427 LLVM_DEBUG(dbgs() << "LV: Found an estimated cost of " << C.firstdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found an estimated cost of "
<< C.first << " for VF " << VF << " For instruction: "
<< I << '\n'; } } while (false)
6428 << " for VF " << VF << " For instruction: " << Ido { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found an estimated cost of "
<< C.first << " for VF " << VF << " For instruction: "
<< I << '\n'; } } while (false)
6429 << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found an estimated cost of "
<< C.first << " for VF " << VF << " For instruction: "
<< I << '\n'; } } while (false)
;
6430 }
6431
6432 // If we are vectorizing a predicated block, it will have been
6433 // if-converted. This means that the block's instructions (aside from
6434 // stores and instructions that may divide by zero) will now be
6435 // unconditionally executed. For the scalar case, we may not always execute
6436 // the predicated block, if it is an if-else block. Thus, scale the block's
6437 // cost by the probability of executing it. blockNeedsPredication from
6438 // Legal is used so as to not include all blocks in tail folded loops.
6439 if (VF.isScalar() && Legal->blockNeedsPredication(BB))
6440 BlockCost.first /= getReciprocalPredBlockProb();
6441
6442 Cost.first += BlockCost.first;
6443 Cost.second |= BlockCost.second;
6444 }
6445
6446 return Cost;
6447}
6448
6449/// Gets Address Access SCEV after verifying that the access pattern
6450/// is loop invariant except the induction variable dependence.
6451///
6452/// This SCEV can be sent to the Target in order to estimate the address
6453/// calculation cost.
6454static const SCEV *getAddressAccessSCEV(
6455 Value *Ptr,
6456 LoopVectorizationLegality *Legal,
6457 PredicatedScalarEvolution &PSE,
6458 const Loop *TheLoop) {
6459
6460 auto *Gep = dyn_cast<GetElementPtrInst>(Ptr);
6461 if (!Gep)
6462 return nullptr;
6463
6464 // We are looking for a gep with all loop invariant indices except for one
6465 // which should be an induction variable.
6466 auto SE = PSE.getSE();
6467 unsigned NumOperands = Gep->getNumOperands();
6468 for (unsigned i = 1; i < NumOperands; ++i) {
6469 Value *Opd = Gep->getOperand(i);
6470 if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) &&
6471 !Legal->isInductionVariable(Opd))
6472 return nullptr;
6473 }
6474
6475 // Now we know we have a GEP ptr, %inv, %ind, %inv. return the Ptr SCEV.
6476 return PSE.getSCEV(Ptr);
6477}
6478
6479static bool isStrideMul(Instruction *I, LoopVectorizationLegality *Legal) {
6480 return Legal->hasStride(I->getOperand(0)) ||
6481 Legal->hasStride(I->getOperand(1));
6482}
6483
6484InstructionCost
6485LoopVectorizationCostModel::getMemInstScalarizationCost(Instruction *I,
6486 ElementCount VF) {
6487 assert(VF.isVector() &&(static_cast <bool> (VF.isVector() && "Scalarization cost of instruction implies vectorization."
) ? void (0) : __assert_fail ("VF.isVector() && \"Scalarization cost of instruction implies vectorization.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6488, __extension__
__PRETTY_FUNCTION__))
6488 "Scalarization cost of instruction implies vectorization.")(static_cast <bool> (VF.isVector() && "Scalarization cost of instruction implies vectorization."
) ? void (0) : __assert_fail ("VF.isVector() && \"Scalarization cost of instruction implies vectorization.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6488, __extension__
__PRETTY_FUNCTION__))
;
6489 if (VF.isScalable())
6490 return InstructionCost::getInvalid();
6491
6492 Type *ValTy = getLoadStoreType(I);
6493 auto SE = PSE.getSE();
6494
6495 unsigned AS = getLoadStoreAddressSpace(I);
6496 Value *Ptr = getLoadStorePointerOperand(I);
6497 Type *PtrTy = ToVectorTy(Ptr->getType(), VF);
6498 // NOTE: PtrTy is a vector to signal `TTI::getAddressComputationCost`
6499 // that it is being called from this specific place.
6500
6501 // Figure out whether the access is strided and get the stride value
6502 // if it's known in compile time
6503 const SCEV *PtrSCEV = getAddressAccessSCEV(Ptr, Legal, PSE, TheLoop);
6504
6505 // Get the cost of the scalar memory instruction and address computation.
6506 InstructionCost Cost =
6507 VF.getKnownMinValue() * TTI.getAddressComputationCost(PtrTy, SE, PtrSCEV);
6508
6509 // Don't pass *I here, since it is scalar but will actually be part of a
6510 // vectorized loop where the user of it is a vectorized instruction.
6511 const Align Alignment = getLoadStoreAlignment(I);
6512 Cost += VF.getKnownMinValue() *
6513 TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(), Alignment,
6514 AS, TTI::TCK_RecipThroughput);
6515
6516 // Get the overhead of the extractelement and insertelement instructions
6517 // we might create due to scalarization.
6518 Cost += getScalarizationOverhead(I, VF);
6519
6520 // If we have a predicated load/store, it will need extra i1 extracts and
6521 // conditional branches, but may not be executed for each vector lane. Scale
6522 // the cost by the probability of executing the predicated block.
6523 if (isPredicatedInst(I, VF)) {
6524 Cost /= getReciprocalPredBlockProb();
6525
6526 // Add the cost of an i1 extract and a branch
6527 auto *Vec_i1Ty =
6528 VectorType::get(IntegerType::getInt1Ty(ValTy->getContext()), VF);
6529 Cost += TTI.getScalarizationOverhead(
6530 Vec_i1Ty, APInt::getAllOnes(VF.getKnownMinValue()),
6531 /*Insert=*/false, /*Extract=*/true);
6532 Cost += TTI.getCFInstrCost(Instruction::Br, TTI::TCK_RecipThroughput);
6533
6534 if (useEmulatedMaskMemRefHack(I, VF))
6535 // Artificially setting to a high enough value to practically disable
6536 // vectorization with such operations.
6537 Cost = 3000000;
6538 }
6539
6540 return Cost;
6541}
6542
6543InstructionCost
6544LoopVectorizationCostModel::getConsecutiveMemOpCost(Instruction *I,
6545 ElementCount VF) {
6546 Type *ValTy = getLoadStoreType(I);
6547 auto *VectorTy = cast<VectorType>(ToVectorTy(ValTy, VF));
6548 Value *Ptr = getLoadStorePointerOperand(I);
6549 unsigned AS = getLoadStoreAddressSpace(I);
6550 int ConsecutiveStride = Legal->isConsecutivePtr(ValTy, Ptr);
6551 enum TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
6552
6553 assert((ConsecutiveStride == 1 || ConsecutiveStride == -1) &&(static_cast <bool> ((ConsecutiveStride == 1 || ConsecutiveStride
== -1) && "Stride should be 1 or -1 for consecutive memory access"
) ? void (0) : __assert_fail ("(ConsecutiveStride == 1 || ConsecutiveStride == -1) && \"Stride should be 1 or -1 for consecutive memory access\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6554, __extension__
__PRETTY_FUNCTION__))
6554 "Stride should be 1 or -1 for consecutive memory access")(static_cast <bool> ((ConsecutiveStride == 1 || ConsecutiveStride
== -1) && "Stride should be 1 or -1 for consecutive memory access"
) ? void (0) : __assert_fail ("(ConsecutiveStride == 1 || ConsecutiveStride == -1) && \"Stride should be 1 or -1 for consecutive memory access\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6554, __extension__
__PRETTY_FUNCTION__))
;
6555 const Align Alignment = getLoadStoreAlignment(I);
6556 InstructionCost Cost = 0;
6557 if (Legal->isMaskRequired(I))
6558 Cost += TTI.getMaskedMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS,
6559 CostKind);
6560 else
6561 Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS,
6562 CostKind, I);
6563
6564 bool Reverse = ConsecutiveStride < 0;
6565 if (Reverse)
6566 Cost +=
6567 TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, VectorTy, None, 0);
6568 return Cost;
6569}
6570
6571InstructionCost
6572LoopVectorizationCostModel::getUniformMemOpCost(Instruction *I,
6573 ElementCount VF) {
6574 assert(Legal->isUniformMemOp(*I))(static_cast <bool> (Legal->isUniformMemOp(*I)) ? void
(0) : __assert_fail ("Legal->isUniformMemOp(*I)", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 6574, __extension__ __PRETTY_FUNCTION__))
;
6575
6576 Type *ValTy = getLoadStoreType(I);
6577 auto *VectorTy = cast<VectorType>(ToVectorTy(ValTy, VF));
6578 const Align Alignment = getLoadStoreAlignment(I);
6579 unsigned AS = getLoadStoreAddressSpace(I);
6580 enum TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
6581 if (isa<LoadInst>(I)) {
6582 return TTI.getAddressComputationCost(ValTy) +
6583 TTI.getMemoryOpCost(Instruction::Load, ValTy, Alignment, AS,
6584 CostKind) +
6585 TTI.getShuffleCost(TargetTransformInfo::SK_Broadcast, VectorTy);
6586 }
6587 StoreInst *SI = cast<StoreInst>(I);
6588
6589 bool isLoopInvariantStoreValue = Legal->isUniform(SI->getValueOperand());
6590 return TTI.getAddressComputationCost(ValTy) +
6591 TTI.getMemoryOpCost(Instruction::Store, ValTy, Alignment, AS,
6592 CostKind) +
6593 (isLoopInvariantStoreValue
6594 ? 0
6595 : TTI.getVectorInstrCost(Instruction::ExtractElement, VectorTy,
6596 VF.getKnownMinValue() - 1));
6597}
6598
6599InstructionCost
6600LoopVectorizationCostModel::getGatherScatterCost(Instruction *I,
6601 ElementCount VF) {
6602 Type *ValTy = getLoadStoreType(I);
6603 auto *VectorTy = cast<VectorType>(ToVectorTy(ValTy, VF));
6604 const Align Alignment = getLoadStoreAlignment(I);
6605 const Value *Ptr = getLoadStorePointerOperand(I);
6606
6607 return TTI.getAddressComputationCost(VectorTy) +
6608 TTI.getGatherScatterOpCost(
6609 I->getOpcode(), VectorTy, Ptr, Legal->isMaskRequired(I), Alignment,
6610 TargetTransformInfo::TCK_RecipThroughput, I);
6611}
6612
6613InstructionCost
6614LoopVectorizationCostModel::getInterleaveGroupCost(Instruction *I,
6615 ElementCount VF) {
6616 // TODO: Once we have support for interleaving with scalable vectors
6617 // we can calculate the cost properly here.
6618 if (VF.isScalable())
6619 return InstructionCost::getInvalid();
6620
6621 Type *ValTy = getLoadStoreType(I);
6622 auto *VectorTy = cast<VectorType>(ToVectorTy(ValTy, VF));
6623 unsigned AS = getLoadStoreAddressSpace(I);
6624
6625 auto Group = getInterleavedAccessGroup(I);
6626 assert(Group && "Fail to get an interleaved access group.")(static_cast <bool> (Group && "Fail to get an interleaved access group."
) ? void (0) : __assert_fail ("Group && \"Fail to get an interleaved access group.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6626, __extension__
__PRETTY_FUNCTION__))
;
6627
6628 unsigned InterleaveFactor = Group->getFactor();
6629 auto *WideVecTy = VectorType::get(ValTy, VF * InterleaveFactor);
6630
6631 // Holds the indices of existing members in the interleaved group.
6632 SmallVector<unsigned, 4> Indices;
6633 for (unsigned IF = 0; IF < InterleaveFactor; IF++)
6634 if (Group->getMember(IF))
6635 Indices.push_back(IF);
6636
6637 // Calculate the cost of the whole interleaved group.
6638 bool UseMaskForGaps =
6639 (Group->requiresScalarEpilogue() && !isScalarEpilogueAllowed()) ||
6640 (isa<StoreInst>(I) && (Group->getNumMembers() < Group->getFactor()));
6641 InstructionCost Cost = TTI.getInterleavedMemoryOpCost(
6642 I->getOpcode(), WideVecTy, Group->getFactor(), Indices, Group->getAlign(),
6643 AS, TTI::TCK_RecipThroughput, Legal->isMaskRequired(I), UseMaskForGaps);
6644
6645 if (Group->isReverse()) {
6646 // TODO: Add support for reversed masked interleaved access.
6647 assert(!Legal->isMaskRequired(I) &&(static_cast <bool> (!Legal->isMaskRequired(I) &&
"Reverse masked interleaved access not supported.") ? void (
0) : __assert_fail ("!Legal->isMaskRequired(I) && \"Reverse masked interleaved access not supported.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6648, __extension__
__PRETTY_FUNCTION__))
6648 "Reverse masked interleaved access not supported.")(static_cast <bool> (!Legal->isMaskRequired(I) &&
"Reverse masked interleaved access not supported.") ? void (
0) : __assert_fail ("!Legal->isMaskRequired(I) && \"Reverse masked interleaved access not supported.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6648, __extension__
__PRETTY_FUNCTION__))
;
6649 Cost +=
6650 Group->getNumMembers() *
6651 TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, VectorTy, None, 0);
6652 }
6653 return Cost;
6654}
6655
6656Optional<InstructionCost> LoopVectorizationCostModel::getReductionPatternCost(
6657 Instruction *I, ElementCount VF, Type *Ty, TTI::TargetCostKind CostKind) {
6658 using namespace llvm::PatternMatch;
6659 // Early exit for no inloop reductions
6660 if (InLoopReductionChains.empty() || VF.isScalar() || !isa<VectorType>(Ty))
6661 return None;
6662 auto *VectorTy = cast<VectorType>(Ty);
6663
6664 // We are looking for a pattern of, and finding the minimal acceptable cost:
6665 // reduce(mul(ext(A), ext(B))) or
6666 // reduce(mul(A, B)) or
6667 // reduce(ext(A)) or
6668 // reduce(A).
6669 // The basic idea is that we walk down the tree to do that, finding the root
6670 // reduction instruction in InLoopReductionImmediateChains. From there we find
6671 // the pattern of mul/ext and test the cost of the entire pattern vs the cost
6672 // of the components. If the reduction cost is lower then we return it for the
6673 // reduction instruction and 0 for the other instructions in the pattern. If
6674 // it is not we return an invalid cost specifying the orignal cost method
6675 // should be used.
6676 Instruction *RetI = I;
6677 if (match(RetI, m_ZExtOrSExt(m_Value()))) {
6678 if (!RetI->hasOneUser())
6679 return None;
6680 RetI = RetI->user_back();
6681 }
6682 if (match(RetI, m_Mul(m_Value(), m_Value())) &&
6683 RetI->user_back()->getOpcode() == Instruction::Add) {
6684 if (!RetI->hasOneUser())
6685 return None;
6686 RetI = RetI->user_back();
6687 }
6688
6689 // Test if the found instruction is a reduction, and if not return an invalid
6690 // cost specifying the parent to use the original cost modelling.
6691 if (!InLoopReductionImmediateChains.count(RetI))
6692 return None;
6693
6694 // Find the reduction this chain is a part of and calculate the basic cost of
6695 // the reduction on its own.
6696 Instruction *LastChain = InLoopReductionImmediateChains[RetI];
6697 Instruction *ReductionPhi = LastChain;
6698 while (!isa<PHINode>(ReductionPhi))
6699 ReductionPhi = InLoopReductionImmediateChains[ReductionPhi];
6700
6701 const RecurrenceDescriptor &RdxDesc =
6702 Legal->getReductionVars().find(cast<PHINode>(ReductionPhi))->second;
6703
6704 InstructionCost BaseCost = TTI.getArithmeticReductionCost(
6705 RdxDesc.getOpcode(), VectorTy, RdxDesc.getFastMathFlags(), CostKind);
6706
6707 // For a call to the llvm.fmuladd intrinsic we need to add the cost of a
6708 // normal fmul instruction to the cost of the fadd reduction.
6709 if (RdxDesc.getRecurrenceKind() == RecurKind::FMulAdd)
6710 BaseCost +=
6711 TTI.getArithmeticInstrCost(Instruction::FMul, VectorTy, CostKind);
6712
6713 // If we're using ordered reductions then we can just return the base cost
6714 // here, since getArithmeticReductionCost calculates the full ordered
6715 // reduction cost when FP reassociation is not allowed.
6716 if (useOrderedReductions(RdxDesc))
6717 return BaseCost;
6718
6719 // Get the operand that was not the reduction chain and match it to one of the
6720 // patterns, returning the better cost if it is found.
6721 Instruction *RedOp = RetI->getOperand(1) == LastChain
6722 ? dyn_cast<Instruction>(RetI->getOperand(0))
6723 : dyn_cast<Instruction>(RetI->getOperand(1));
6724
6725 VectorTy = VectorType::get(I->getOperand(0)->getType(), VectorTy);
6726
6727 Instruction *Op0, *Op1;
6728 if (RedOp &&
6729 match(RedOp,
6730 m_ZExtOrSExt(m_Mul(m_Instruction(Op0), m_Instruction(Op1)))) &&
6731 match(Op0, m_ZExtOrSExt(m_Value())) &&
6732 Op0->getOpcode() == Op1->getOpcode() &&
6733 Op0->getOperand(0)->getType() == Op1->getOperand(0)->getType() &&
6734 !TheLoop->isLoopInvariant(Op0) && !TheLoop->isLoopInvariant(Op1) &&
6735 (Op0->getOpcode() == RedOp->getOpcode() || Op0 == Op1)) {
6736
6737 // Matched reduce(ext(mul(ext(A), ext(B)))
6738 // Note that the extend opcodes need to all match, or if A==B they will have
6739 // been converted to zext(mul(sext(A), sext(A))) as it is known positive,
6740 // which is equally fine.
6741 bool IsUnsigned = isa<ZExtInst>(Op0);
6742 auto *ExtType = VectorType::get(Op0->getOperand(0)->getType(), VectorTy);
6743 auto *MulType = VectorType::get(Op0->getType(), VectorTy);
6744
6745 InstructionCost ExtCost =
6746 TTI.getCastInstrCost(Op0->getOpcode(), MulType, ExtType,
6747 TTI::CastContextHint::None, CostKind, Op0);
6748 InstructionCost MulCost =
6749 TTI.getArithmeticInstrCost(Instruction::Mul, MulType, CostKind);
6750 InstructionCost Ext2Cost =
6751 TTI.getCastInstrCost(RedOp->getOpcode(), VectorTy, MulType,
6752 TTI::CastContextHint::None, CostKind, RedOp);
6753
6754 InstructionCost RedCost = TTI.getExtendedAddReductionCost(
6755 /*IsMLA=*/true, IsUnsigned, RdxDesc.getRecurrenceType(), ExtType,
6756 CostKind);
6757
6758 if (RedCost.isValid() &&
6759 RedCost < ExtCost * 2 + MulCost + Ext2Cost + BaseCost)
6760 return I == RetI ? RedCost : 0;
6761 } else if (RedOp && match(RedOp, m_ZExtOrSExt(m_Value())) &&
6762 !TheLoop->isLoopInvariant(RedOp)) {
6763 // Matched reduce(ext(A))
6764 bool IsUnsigned = isa<ZExtInst>(RedOp);
6765 auto *ExtType = VectorType::get(RedOp->getOperand(0)->getType(), VectorTy);
6766 InstructionCost RedCost = TTI.getExtendedAddReductionCost(
6767 /*IsMLA=*/false, IsUnsigned, RdxDesc.getRecurrenceType(), ExtType,
6768 CostKind);
6769
6770 InstructionCost ExtCost =
6771 TTI.getCastInstrCost(RedOp->getOpcode(), VectorTy, ExtType,
6772 TTI::CastContextHint::None, CostKind, RedOp);
6773 if (RedCost.isValid() && RedCost < BaseCost + ExtCost)
6774 return I == RetI ? RedCost : 0;
6775 } else if (RedOp &&
6776 match(RedOp, m_Mul(m_Instruction(Op0), m_Instruction(Op1)))) {
6777 if (match(Op0, m_ZExtOrSExt(m_Value())) &&
6778 Op0->getOpcode() == Op1->getOpcode() &&
6779 !TheLoop->isLoopInvariant(Op0) && !TheLoop->isLoopInvariant(Op1)) {
6780 bool IsUnsigned = isa<ZExtInst>(Op0);
6781 Type *Op0Ty = Op0->getOperand(0)->getType();
6782 Type *Op1Ty = Op1->getOperand(0)->getType();
6783 Type *LargestOpTy =
6784 Op0Ty->getIntegerBitWidth() < Op1Ty->getIntegerBitWidth() ? Op1Ty
6785 : Op0Ty;
6786 auto *ExtType = VectorType::get(LargestOpTy, VectorTy);
6787
6788 // Matched reduce(mul(ext(A), ext(B))), where the two ext may be of
6789 // different sizes. We take the largest type as the ext to reduce, and add
6790 // the remaining cost as, for example reduce(mul(ext(ext(A)), ext(B))).
6791 InstructionCost ExtCost0 = TTI.getCastInstrCost(
6792 Op0->getOpcode(), VectorTy, VectorType::get(Op0Ty, VectorTy),
6793 TTI::CastContextHint::None, CostKind, Op0);
6794 InstructionCost ExtCost1 = TTI.getCastInstrCost(
6795 Op1->getOpcode(), VectorTy, VectorType::get(Op1Ty, VectorTy),
6796 TTI::CastContextHint::None, CostKind, Op1);
6797 InstructionCost MulCost =
6798 TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy, CostKind);
6799
6800 InstructionCost RedCost = TTI.getExtendedAddReductionCost(
6801 /*IsMLA=*/true, IsUnsigned, RdxDesc.getRecurrenceType(), ExtType,
6802 CostKind);
6803 InstructionCost ExtraExtCost = 0;
6804 if (Op0Ty != LargestOpTy || Op1Ty != LargestOpTy) {
6805 Instruction *ExtraExtOp = (Op0Ty != LargestOpTy) ? Op0 : Op1;
6806 ExtraExtCost = TTI.getCastInstrCost(
6807 ExtraExtOp->getOpcode(), ExtType,
6808 VectorType::get(ExtraExtOp->getOperand(0)->getType(), VectorTy),
6809 TTI::CastContextHint::None, CostKind, ExtraExtOp);
6810 }
6811
6812 if (RedCost.isValid() &&
6813 (RedCost + ExtraExtCost) < (ExtCost0 + ExtCost1 + MulCost + BaseCost))
6814 return I == RetI ? RedCost : 0;
6815 } else if (!match(I, m_ZExtOrSExt(m_Value()))) {
6816 // Matched reduce(mul())
6817 InstructionCost MulCost =
6818 TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy, CostKind);
6819
6820 InstructionCost RedCost = TTI.getExtendedAddReductionCost(
6821 /*IsMLA=*/true, true, RdxDesc.getRecurrenceType(), VectorTy,
6822 CostKind);
6823
6824 if (RedCost.isValid() && RedCost < MulCost + BaseCost)
6825 return I == RetI ? RedCost : 0;
6826 }
6827 }
6828
6829 return I == RetI ? Optional<InstructionCost>(BaseCost) : None;
6830}
6831
6832InstructionCost
6833LoopVectorizationCostModel::getMemoryInstructionCost(Instruction *I,
6834 ElementCount VF) {
6835 // Calculate scalar cost only. Vectorization cost should be ready at this
6836 // moment.
6837 if (VF.isScalar()) {
6838 Type *ValTy = getLoadStoreType(I);
6839 const Align Alignment = getLoadStoreAlignment(I);
6840 unsigned AS = getLoadStoreAddressSpace(I);
6841
6842 return TTI.getAddressComputationCost(ValTy) +
6843 TTI.getMemoryOpCost(I->getOpcode(), ValTy, Alignment, AS,
6844 TTI::TCK_RecipThroughput, I);
6845 }
6846 return getWideningCost(I, VF);
6847}
6848
6849LoopVectorizationCostModel::VectorizationCostTy
6850LoopVectorizationCostModel::getInstructionCost(Instruction *I,
6851 ElementCount VF) {
6852 // If we know that this instruction will remain uniform, check the cost of
6853 // the scalar version.
6854 if (isUniformAfterVectorization(I, VF))
6855 VF = ElementCount::getFixed(1);
6856
6857 if (VF.isVector() && isProfitableToScalarize(I, VF))
6858 return VectorizationCostTy(InstsToScalarize[VF][I], false);
6859
6860 // Forced scalars do not have any scalarization overhead.
6861 auto ForcedScalar = ForcedScalars.find(VF);
6862 if (VF.isVector() && ForcedScalar != ForcedScalars.end()) {
6863 auto InstSet = ForcedScalar->second;
6864 if (InstSet.count(I))
6865 return VectorizationCostTy(
6866 (getInstructionCost(I, ElementCount::getFixed(1)).first *
6867 VF.getKnownMinValue()),
6868 false);
6869 }
6870
6871 Type *VectorTy;
6872 InstructionCost C = getInstructionCost(I, VF, VectorTy);
6873
6874 bool TypeNotScalarized = false;
6875 if (VF.isVector() && VectorTy->isVectorTy()) {
6876 unsigned NumParts = TTI.getNumberOfParts(VectorTy);
6877 if (NumParts)
6878 TypeNotScalarized = NumParts < VF.getKnownMinValue();
6879 else
6880 C = InstructionCost::getInvalid();
6881 }
6882 return VectorizationCostTy(C, TypeNotScalarized);
6883}
6884
6885InstructionCost
6886LoopVectorizationCostModel::getScalarizationOverhead(Instruction *I,
6887 ElementCount VF) const {
6888
6889 // There is no mechanism yet to create a scalable scalarization loop,
6890 // so this is currently Invalid.
6891 if (VF.isScalable())
6892 return InstructionCost::getInvalid();
6893
6894 if (VF.isScalar())
6895 return 0;
6896
6897 InstructionCost Cost = 0;
6898 Type *RetTy = ToVectorTy(I->getType(), VF);
6899 if (!RetTy->isVoidTy() &&
6900 (!isa<LoadInst>(I) || !TTI.supportsEfficientVectorElementLoadStore()))
6901 Cost += TTI.getScalarizationOverhead(
6902 cast<VectorType>(RetTy), APInt::getAllOnes(VF.getKnownMinValue()), true,
6903 false);
6904
6905 // Some targets keep addresses scalar.
6906 if (isa<LoadInst>(I) && !TTI.prefersVectorizedAddressing())
6907 return Cost;
6908
6909 // Some targets support efficient element stores.
6910 if (isa<StoreInst>(I) && TTI.supportsEfficientVectorElementLoadStore())
6911 return Cost;
6912
6913 // Collect operands to consider.
6914 CallInst *CI = dyn_cast<CallInst>(I);
6915 Instruction::op_range Ops = CI ? CI->args() : I->operands();
6916
6917 // Skip operands that do not require extraction/scalarization and do not incur
6918 // any overhead.
6919 SmallVector<Type *> Tys;
6920 for (auto *V : filterExtractingOperands(Ops, VF))
6921 Tys.push_back(MaybeVectorizeType(V->getType(), VF));
6922 return Cost + TTI.getOperandsScalarizationOverhead(
6923 filterExtractingOperands(Ops, VF), Tys);
6924}
6925
6926void LoopVectorizationCostModel::setCostBasedWideningDecision(ElementCount VF) {
6927 if (VF.isScalar())
6928 return;
6929 NumPredStores = 0;
6930 for (BasicBlock *BB : TheLoop->blocks()) {
6931 // For each instruction in the old loop.
6932 for (Instruction &I : *BB) {
6933 Value *Ptr = getLoadStorePointerOperand(&I);
6934 if (!Ptr)
6935 continue;
6936
6937 // TODO: We should generate better code and update the cost model for
6938 // predicated uniform stores. Today they are treated as any other
6939 // predicated store (see added test cases in
6940 // invariant-store-vectorization.ll).
6941 if (isa<StoreInst>(&I) && isScalarWithPredication(&I, VF))
6942 NumPredStores++;
6943
6944 if (Legal->isUniformMemOp(I)) {
6945 // TODO: Avoid replicating loads and stores instead of
6946 // relying on instcombine to remove them.
6947 // Load: Scalar load + broadcast
6948 // Store: Scalar store + isLoopInvariantStoreValue ? 0 : extract
6949 InstructionCost Cost;
6950 if (isa<StoreInst>(&I) && VF.isScalable() &&
6951 isLegalGatherOrScatter(&I, VF)) {
6952 Cost = getGatherScatterCost(&I, VF);
6953 setWideningDecision(&I, VF, CM_GatherScatter, Cost);
6954 } else {
6955 assert((isa<LoadInst>(&I) || !VF.isScalable()) &&(static_cast <bool> ((isa<LoadInst>(&I) || !VF
.isScalable()) && "Cannot yet scalarize uniform stores"
) ? void (0) : __assert_fail ("(isa<LoadInst>(&I) || !VF.isScalable()) && \"Cannot yet scalarize uniform stores\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6956, __extension__
__PRETTY_FUNCTION__))
6956 "Cannot yet scalarize uniform stores")(static_cast <bool> ((isa<LoadInst>(&I) || !VF
.isScalable()) && "Cannot yet scalarize uniform stores"
) ? void (0) : __assert_fail ("(isa<LoadInst>(&I) || !VF.isScalable()) && \"Cannot yet scalarize uniform stores\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6956, __extension__
__PRETTY_FUNCTION__))
;
6957 Cost = getUniformMemOpCost(&I, VF);
6958 setWideningDecision(&I, VF, CM_Scalarize, Cost);
6959 }
6960 continue;
6961 }
6962
6963 // We assume that widening is the best solution when possible.
6964 if (memoryInstructionCanBeWidened(&I, VF)) {
6965 InstructionCost Cost = getConsecutiveMemOpCost(&I, VF);
6966 int ConsecutiveStride = Legal->isConsecutivePtr(
6967 getLoadStoreType(&I), getLoadStorePointerOperand(&I));
6968 assert((ConsecutiveStride == 1 || ConsecutiveStride == -1) &&(static_cast <bool> ((ConsecutiveStride == 1 || ConsecutiveStride
== -1) && "Expected consecutive stride.") ? void (0)
: __assert_fail ("(ConsecutiveStride == 1 || ConsecutiveStride == -1) && \"Expected consecutive stride.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6969, __extension__
__PRETTY_FUNCTION__))
6969 "Expected consecutive stride.")(static_cast <bool> ((ConsecutiveStride == 1 || ConsecutiveStride
== -1) && "Expected consecutive stride.") ? void (0)
: __assert_fail ("(ConsecutiveStride == 1 || ConsecutiveStride == -1) && \"Expected consecutive stride.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6969, __extension__
__PRETTY_FUNCTION__))
;
6970 InstWidening Decision =
6971 ConsecutiveStride == 1 ? CM_Widen : CM_Widen_Reverse;
6972 setWideningDecision(&I, VF, Decision, Cost);
6973 continue;
6974 }
6975
6976 // Choose between Interleaving, Gather/Scatter or Scalarization.
6977 InstructionCost InterleaveCost = InstructionCost::getInvalid();
6978 unsigned NumAccesses = 1;
6979 if (isAccessInterleaved(&I)) {
6980 auto Group = getInterleavedAccessGroup(&I);
6981 assert(Group && "Fail to get an interleaved access group.")(static_cast <bool> (Group && "Fail to get an interleaved access group."
) ? void (0) : __assert_fail ("Group && \"Fail to get an interleaved access group.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 6981, __extension__
__PRETTY_FUNCTION__))
;
6982
6983 // Make one decision for the whole group.
6984 if (getWideningDecision(&I, VF) != CM_Unknown)
6985 continue;
6986
6987 NumAccesses = Group->getNumMembers();
6988 if (interleavedAccessCanBeWidened(&I, VF))
6989 InterleaveCost = getInterleaveGroupCost(&I, VF);
6990 }
6991
6992 InstructionCost GatherScatterCost =
6993 isLegalGatherOrScatter(&I, VF)
6994 ? getGatherScatterCost(&I, VF) * NumAccesses
6995 : InstructionCost::getInvalid();
6996
6997 InstructionCost ScalarizationCost =
6998 getMemInstScalarizationCost(&I, VF) * NumAccesses;
6999
7000 // Choose better solution for the current VF,
7001 // write down this decision and use it during vectorization.
7002 InstructionCost Cost;
7003 InstWidening Decision;
7004 if (InterleaveCost <= GatherScatterCost &&
7005 InterleaveCost < ScalarizationCost) {
7006 Decision = CM_Interleave;
7007 Cost = InterleaveCost;
7008 } else if (GatherScatterCost < ScalarizationCost) {
7009 Decision = CM_GatherScatter;
7010 Cost = GatherScatterCost;
7011 } else {
7012 Decision = CM_Scalarize;
7013 Cost = ScalarizationCost;
7014 }
7015 // If the instructions belongs to an interleave group, the whole group
7016 // receives the same decision. The whole group receives the cost, but
7017 // the cost will actually be assigned to one instruction.
7018 if (auto Group = getInterleavedAccessGroup(&I))
7019 setWideningDecision(Group, VF, Decision, Cost);
7020 else
7021 setWideningDecision(&I, VF, Decision, Cost);
7022 }
7023 }
7024
7025 // Make sure that any load of address and any other address computation
7026 // remains scalar unless there is gather/scatter support. This avoids
7027 // inevitable extracts into address registers, and also has the benefit of
7028 // activating LSR more, since that pass can't optimize vectorized
7029 // addresses.
7030 if (TTI.prefersVectorizedAddressing())
7031 return;
7032
7033 // Start with all scalar pointer uses.
7034 SmallPtrSet<Instruction *, 8> AddrDefs;
7035 for (BasicBlock *BB : TheLoop->blocks())
7036 for (Instruction &I : *BB) {
7037 Instruction *PtrDef =
7038 dyn_cast_or_null<Instruction>(getLoadStorePointerOperand(&I));
7039 if (PtrDef && TheLoop->contains(PtrDef) &&
7040 getWideningDecision(&I, VF) != CM_GatherScatter)
7041 AddrDefs.insert(PtrDef);
7042 }
7043
7044 // Add all instructions used to generate the addresses.
7045 SmallVector<Instruction *, 4> Worklist;
7046 append_range(Worklist, AddrDefs);
7047 while (!Worklist.empty()) {
7048 Instruction *I = Worklist.pop_back_val();
7049 for (auto &Op : I->operands())
7050 if (auto *InstOp = dyn_cast<Instruction>(Op))
7051 if ((InstOp->getParent() == I->getParent()) && !isa<PHINode>(InstOp) &&
7052 AddrDefs.insert(InstOp).second)
7053 Worklist.push_back(InstOp);
7054 }
7055
7056 for (auto *I : AddrDefs) {
7057 if (isa<LoadInst>(I)) {
7058 // Setting the desired widening decision should ideally be handled in
7059 // by cost functions, but since this involves the task of finding out
7060 // if the loaded register is involved in an address computation, it is
7061 // instead changed here when we know this is the case.
7062 InstWidening Decision = getWideningDecision(I, VF);
7063 if (Decision == CM_Widen || Decision == CM_Widen_Reverse)
7064 // Scalarize a widened load of address.
7065 setWideningDecision(
7066 I, VF, CM_Scalarize,
7067 (VF.getKnownMinValue() *
7068 getMemoryInstructionCost(I, ElementCount::getFixed(1))));
7069 else if (auto Group = getInterleavedAccessGroup(I)) {
7070 // Scalarize an interleave group of address loads.
7071 for (unsigned I = 0; I < Group->getFactor(); ++I) {
7072 if (Instruction *Member = Group->getMember(I))
7073 setWideningDecision(
7074 Member, VF, CM_Scalarize,
7075 (VF.getKnownMinValue() *
7076 getMemoryInstructionCost(Member, ElementCount::getFixed(1))));
7077 }
7078 }
7079 } else
7080 // Make sure I gets scalarized and a cost estimate without
7081 // scalarization overhead.
7082 ForcedScalars[VF].insert(I);
7083 }
7084}
7085
7086InstructionCost
7087LoopVectorizationCostModel::getInstructionCost(Instruction *I, ElementCount VF,
7088 Type *&VectorTy) {
7089 Type *RetTy = I->getType();
7090 if (canTruncateToMinimalBitwidth(I, VF))
7091 RetTy = IntegerType::get(RetTy->getContext(), MinBWs[I]);
7092 auto SE = PSE.getSE();
7093 TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
7094
7095 auto hasSingleCopyAfterVectorization = [this](Instruction *I,
7096 ElementCount VF) -> bool {
7097 if (VF.isScalar())
7098 return true;
7099
7100 auto Scalarized = InstsToScalarize.find(VF);
7101 assert(Scalarized != InstsToScalarize.end() &&(static_cast <bool> (Scalarized != InstsToScalarize.end
() && "VF not yet analyzed for scalarization profitability"
) ? void (0) : __assert_fail ("Scalarized != InstsToScalarize.end() && \"VF not yet analyzed for scalarization profitability\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7102, __extension__
__PRETTY_FUNCTION__))
7102 "VF not yet analyzed for scalarization profitability")(static_cast <bool> (Scalarized != InstsToScalarize.end
() && "VF not yet analyzed for scalarization profitability"
) ? void (0) : __assert_fail ("Scalarized != InstsToScalarize.end() && \"VF not yet analyzed for scalarization profitability\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7102, __extension__
__PRETTY_FUNCTION__))
;
7103 return !Scalarized->second.count(I) &&
7104 llvm::all_of(I->users(), [&](User *U) {
7105 auto *UI = cast<Instruction>(U);
7106 return !Scalarized->second.count(UI);
7107 });
7108 };
7109 (void) hasSingleCopyAfterVectorization;
7110
7111 if (isScalarAfterVectorization(I, VF)) {
7112 // With the exception of GEPs and PHIs, after scalarization there should
7113 // only be one copy of the instruction generated in the loop. This is
7114 // because the VF is either 1, or any instructions that need scalarizing
7115 // have already been dealt with by the the time we get here. As a result,
7116 // it means we don't have to multiply the instruction cost by VF.
7117 assert(I->getOpcode() == Instruction::GetElementPtr ||(static_cast <bool> (I->getOpcode() == Instruction::
GetElementPtr || I->getOpcode() == Instruction::PHI || (I->
getOpcode() == Instruction::BitCast && I->getType(
)->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF
)) ? void (0) : __assert_fail ("I->getOpcode() == Instruction::GetElementPtr || I->getOpcode() == Instruction::PHI || (I->getOpcode() == Instruction::BitCast && I->getType()->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF)"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7121, __extension__
__PRETTY_FUNCTION__))
7118 I->getOpcode() == Instruction::PHI ||(static_cast <bool> (I->getOpcode() == Instruction::
GetElementPtr || I->getOpcode() == Instruction::PHI || (I->
getOpcode() == Instruction::BitCast && I->getType(
)->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF
)) ? void (0) : __assert_fail ("I->getOpcode() == Instruction::GetElementPtr || I->getOpcode() == Instruction::PHI || (I->getOpcode() == Instruction::BitCast && I->getType()->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF)"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7121, __extension__
__PRETTY_FUNCTION__))
7119 (I->getOpcode() == Instruction::BitCast &&(static_cast <bool> (I->getOpcode() == Instruction::
GetElementPtr || I->getOpcode() == Instruction::PHI || (I->
getOpcode() == Instruction::BitCast && I->getType(
)->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF
)) ? void (0) : __assert_fail ("I->getOpcode() == Instruction::GetElementPtr || I->getOpcode() == Instruction::PHI || (I->getOpcode() == Instruction::BitCast && I->getType()->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF)"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7121, __extension__
__PRETTY_FUNCTION__))
7120 I->getType()->isPointerTy()) ||(static_cast <bool> (I->getOpcode() == Instruction::
GetElementPtr || I->getOpcode() == Instruction::PHI || (I->
getOpcode() == Instruction::BitCast && I->getType(
)->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF
)) ? void (0) : __assert_fail ("I->getOpcode() == Instruction::GetElementPtr || I->getOpcode() == Instruction::PHI || (I->getOpcode() == Instruction::BitCast && I->getType()->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF)"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7121, __extension__
__PRETTY_FUNCTION__))
7121 hasSingleCopyAfterVectorization(I, VF))(static_cast <bool> (I->getOpcode() == Instruction::
GetElementPtr || I->getOpcode() == Instruction::PHI || (I->
getOpcode() == Instruction::BitCast && I->getType(
)->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF
)) ? void (0) : __assert_fail ("I->getOpcode() == Instruction::GetElementPtr || I->getOpcode() == Instruction::PHI || (I->getOpcode() == Instruction::BitCast && I->getType()->isPointerTy()) || hasSingleCopyAfterVectorization(I, VF)"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7121, __extension__
__PRETTY_FUNCTION__))
;
7122 VectorTy = RetTy;
7123 } else
7124 VectorTy = ToVectorTy(RetTy, VF);
7125
7126 // TODO: We need to estimate the cost of intrinsic calls.
7127 switch (I->getOpcode()) {
7128 case Instruction::GetElementPtr:
7129 // We mark this instruction as zero-cost because the cost of GEPs in
7130 // vectorized code depends on whether the corresponding memory instruction
7131 // is scalarized or not. Therefore, we handle GEPs with the memory
7132 // instruction cost.
7133 return 0;
7134 case Instruction::Br: {
7135 // In cases of scalarized and predicated instructions, there will be VF
7136 // predicated blocks in the vectorized loop. Each branch around these
7137 // blocks requires also an extract of its vector compare i1 element.
7138 bool ScalarPredicatedBB = false;
7139 BranchInst *BI = cast<BranchInst>(I);
7140 if (VF.isVector() && BI->isConditional() &&
7141 (PredicatedBBsAfterVectorization.count(BI->getSuccessor(0)) ||
7142 PredicatedBBsAfterVectorization.count(BI->getSuccessor(1))))
7143 ScalarPredicatedBB = true;
7144
7145 if (ScalarPredicatedBB) {
7146 // Not possible to scalarize scalable vector with predicated instructions.
7147 if (VF.isScalable())
7148 return InstructionCost::getInvalid();
7149 // Return cost for branches around scalarized and predicated blocks.
7150 auto *Vec_i1Ty =
7151 VectorType::get(IntegerType::getInt1Ty(RetTy->getContext()), VF);
7152 return (
7153 TTI.getScalarizationOverhead(
7154 Vec_i1Ty, APInt::getAllOnes(VF.getFixedValue()), false, true) +
7155 (TTI.getCFInstrCost(Instruction::Br, CostKind) * VF.getFixedValue()));
7156 } else if (I->getParent() == TheLoop->getLoopLatch() || VF.isScalar())
7157 // The back-edge branch will remain, as will all scalar branches.
7158 return TTI.getCFInstrCost(Instruction::Br, CostKind);
7159 else
7160 // This branch will be eliminated by if-conversion.
7161 return 0;
7162 // Note: We currently assume zero cost for an unconditional branch inside
7163 // a predicated block since it will become a fall-through, although we
7164 // may decide in the future to call TTI for all branches.
7165 }
7166 case Instruction::PHI: {
7167 auto *Phi = cast<PHINode>(I);
7168
7169 // First-order recurrences are replaced by vector shuffles inside the loop.
7170 // NOTE: Don't use ToVectorTy as SK_ExtractSubvector expects a vector type.
7171 if (VF.isVector() && Legal->isFirstOrderRecurrence(Phi))
7172 return TTI.getShuffleCost(
7173 TargetTransformInfo::SK_ExtractSubvector, cast<VectorType>(VectorTy),
7174 None, VF.getKnownMinValue() - 1, FixedVectorType::get(RetTy, 1));
7175
7176 // Phi nodes in non-header blocks (not inductions, reductions, etc.) are
7177 // converted into select instructions. We require N - 1 selects per phi
7178 // node, where N is the number of incoming values.
7179 if (VF.isVector() && Phi->getParent() != TheLoop->getHeader())
7180 return (Phi->getNumIncomingValues() - 1) *
7181 TTI.getCmpSelInstrCost(
7182 Instruction::Select, ToVectorTy(Phi->getType(), VF),
7183 ToVectorTy(Type::getInt1Ty(Phi->getContext()), VF),
7184 CmpInst::BAD_ICMP_PREDICATE, CostKind);
7185
7186 return TTI.getCFInstrCost(Instruction::PHI, CostKind);
7187 }
7188 case Instruction::UDiv:
7189 case Instruction::SDiv:
7190 case Instruction::URem:
7191 case Instruction::SRem:
7192 // If we have a predicated instruction, it may not be executed for each
7193 // vector lane. Get the scalarization cost and scale this amount by the
7194 // probability of executing the predicated block. If the instruction is not
7195 // predicated, we fall through to the next case.
7196 if (VF.isVector() && isScalarWithPredication(I, VF)) {
7197 InstructionCost Cost = 0;
7198
7199 // These instructions have a non-void type, so account for the phi nodes
7200 // that we will create. This cost is likely to be zero. The phi node
7201 // cost, if any, should be scaled by the block probability because it
7202 // models a copy at the end of each predicated block.
7203 Cost += VF.getKnownMinValue() *
7204 TTI.getCFInstrCost(Instruction::PHI, CostKind);
7205
7206 // The cost of the non-predicated instruction.
7207 Cost += VF.getKnownMinValue() *
7208 TTI.getArithmeticInstrCost(I->getOpcode(), RetTy, CostKind);
7209
7210 // The cost of insertelement and extractelement instructions needed for
7211 // scalarization.
7212 Cost += getScalarizationOverhead(I, VF);
7213
7214 // Scale the cost by the probability of executing the predicated blocks.
7215 // This assumes the predicated block for each vector lane is equally
7216 // likely.
7217 return Cost / getReciprocalPredBlockProb();
7218 }
7219 LLVM_FALLTHROUGH[[gnu::fallthrough]];
7220 case Instruction::Add:
7221 case Instruction::FAdd:
7222 case Instruction::Sub:
7223 case Instruction::FSub:
7224 case Instruction::Mul:
7225 case Instruction::FMul:
7226 case Instruction::FDiv:
7227 case Instruction::FRem:
7228 case Instruction::Shl:
7229 case Instruction::LShr:
7230 case Instruction::AShr:
7231 case Instruction::And:
7232 case Instruction::Or:
7233 case Instruction::Xor: {
7234 // Since we will replace the stride by 1 the multiplication should go away.
7235 if (I->getOpcode() == Instruction::Mul && isStrideMul(I, Legal))
7236 return 0;
7237
7238 // Detect reduction patterns
7239 if (auto RedCost = getReductionPatternCost(I, VF, VectorTy, CostKind))
7240 return *RedCost;
7241
7242 // Certain instructions can be cheaper to vectorize if they have a constant
7243 // second vector operand. One example of this are shifts on x86.
7244 Value *Op2 = I->getOperand(1);
7245 TargetTransformInfo::OperandValueProperties Op2VP;
7246 TargetTransformInfo::OperandValueKind Op2VK =
7247 TTI.getOperandInfo(Op2, Op2VP);
7248 if (Op2VK == TargetTransformInfo::OK_AnyValue && Legal->isUniform(Op2))
7249 Op2VK = TargetTransformInfo::OK_UniformValue;
7250
7251 SmallVector<const Value *, 4> Operands(I->operand_values());
7252 return TTI.getArithmeticInstrCost(
7253 I->getOpcode(), VectorTy, CostKind, TargetTransformInfo::OK_AnyValue,
7254 Op2VK, TargetTransformInfo::OP_None, Op2VP, Operands, I);
7255 }
7256 case Instruction::FNeg: {
7257 return TTI.getArithmeticInstrCost(
7258 I->getOpcode(), VectorTy, CostKind, TargetTransformInfo::OK_AnyValue,
7259 TargetTransformInfo::OK_AnyValue, TargetTransformInfo::OP_None,
7260 TargetTransformInfo::OP_None, I->getOperand(0), I);
7261 }
7262 case Instruction::Select: {
7263 SelectInst *SI = cast<SelectInst>(I);
7264 const SCEV *CondSCEV = SE->getSCEV(SI->getCondition());
7265 bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop));
7266
7267 const Value *Op0, *Op1;
7268 using namespace llvm::PatternMatch;
7269 if (!ScalarCond && (match(I, m_LogicalAnd(m_Value(Op0), m_Value(Op1))) ||
7270 match(I, m_LogicalOr(m_Value(Op0), m_Value(Op1))))) {
7271 // select x, y, false --> x & y
7272 // select x, true, y --> x | y
7273 TTI::OperandValueProperties Op1VP = TTI::OP_None;
7274 TTI::OperandValueProperties Op2VP = TTI::OP_None;
7275 TTI::OperandValueKind Op1VK = TTI::getOperandInfo(Op0, Op1VP);
7276 TTI::OperandValueKind Op2VK = TTI::getOperandInfo(Op1, Op2VP);
7277 assert(Op0->getType()->getScalarSizeInBits() == 1 &&(static_cast <bool> (Op0->getType()->getScalarSizeInBits
() == 1 && Op1->getType()->getScalarSizeInBits(
) == 1) ? void (0) : __assert_fail ("Op0->getType()->getScalarSizeInBits() == 1 && Op1->getType()->getScalarSizeInBits() == 1"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7278, __extension__
__PRETTY_FUNCTION__))
7278 Op1->getType()->getScalarSizeInBits() == 1)(static_cast <bool> (Op0->getType()->getScalarSizeInBits
() == 1 && Op1->getType()->getScalarSizeInBits(
) == 1) ? void (0) : __assert_fail ("Op0->getType()->getScalarSizeInBits() == 1 && Op1->getType()->getScalarSizeInBits() == 1"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7278, __extension__
__PRETTY_FUNCTION__))
;
7279
7280 SmallVector<const Value *, 2> Operands{Op0, Op1};
7281 return TTI.getArithmeticInstrCost(
7282 match(I, m_LogicalOr()) ? Instruction::Or : Instruction::And, VectorTy,
7283 CostKind, Op1VK, Op2VK, Op1VP, Op2VP, Operands, I);
7284 }
7285
7286 Type *CondTy = SI->getCondition()->getType();
7287 if (!ScalarCond)
7288 CondTy = VectorType::get(CondTy, VF);
7289
7290 CmpInst::Predicate Pred = CmpInst::BAD_ICMP_PREDICATE;
7291 if (auto *Cmp = dyn_cast<CmpInst>(SI->getCondition()))
7292 Pred = Cmp->getPredicate();
7293 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy, Pred,
7294 CostKind, I);
7295 }
7296 case Instruction::ICmp:
7297 case Instruction::FCmp: {
7298 Type *ValTy = I->getOperand(0)->getType();
7299 Instruction *Op0AsInstruction = dyn_cast<Instruction>(I->getOperand(0));
7300 if (canTruncateToMinimalBitwidth(Op0AsInstruction, VF))
7301 ValTy = IntegerType::get(ValTy->getContext(), MinBWs[Op0AsInstruction]);
7302 VectorTy = ToVectorTy(ValTy, VF);
7303 return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, nullptr,
7304 cast<CmpInst>(I)->getPredicate(), CostKind,
7305 I);
7306 }
7307 case Instruction::Store:
7308 case Instruction::Load: {
7309 ElementCount Width = VF;
7310 if (Width.isVector()) {
7311 InstWidening Decision = getWideningDecision(I, Width);
7312 assert(Decision != CM_Unknown &&(static_cast <bool> (Decision != CM_Unknown && "CM decision should be taken at this point"
) ? void (0) : __assert_fail ("Decision != CM_Unknown && \"CM decision should be taken at this point\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7313, __extension__
__PRETTY_FUNCTION__))
7313 "CM decision should be taken at this point")(static_cast <bool> (Decision != CM_Unknown && "CM decision should be taken at this point"
) ? void (0) : __assert_fail ("Decision != CM_Unknown && \"CM decision should be taken at this point\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7313, __extension__
__PRETTY_FUNCTION__))
;
7314 if (Decision == CM_Scalarize)
7315 Width = ElementCount::getFixed(1);
7316 }
7317 VectorTy = ToVectorTy(getLoadStoreType(I), Width);
7318 return getMemoryInstructionCost(I, VF);
7319 }
7320 case Instruction::BitCast:
7321 if (I->getType()->isPointerTy())
7322 return 0;
7323 LLVM_FALLTHROUGH[[gnu::fallthrough]];
7324 case Instruction::ZExt:
7325 case Instruction::SExt:
7326 case Instruction::FPToUI:
7327 case Instruction::FPToSI:
7328 case Instruction::FPExt:
7329 case Instruction::PtrToInt:
7330 case Instruction::IntToPtr:
7331 case Instruction::SIToFP:
7332 case Instruction::UIToFP:
7333 case Instruction::Trunc:
7334 case Instruction::FPTrunc: {
7335 // Computes the CastContextHint from a Load/Store instruction.
7336 auto ComputeCCH = [&](Instruction *I) -> TTI::CastContextHint {
7337 assert((isa<LoadInst>(I) || isa<StoreInst>(I)) &&(static_cast <bool> ((isa<LoadInst>(I) || isa<
StoreInst>(I)) && "Expected a load or a store!") ?
void (0) : __assert_fail ("(isa<LoadInst>(I) || isa<StoreInst>(I)) && \"Expected a load or a store!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7338, __extension__
__PRETTY_FUNCTION__))
7338 "Expected a load or a store!")(static_cast <bool> ((isa<LoadInst>(I) || isa<
StoreInst>(I)) && "Expected a load or a store!") ?
void (0) : __assert_fail ("(isa<LoadInst>(I) || isa<StoreInst>(I)) && \"Expected a load or a store!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7338, __extension__
__PRETTY_FUNCTION__))
;
7339
7340 if (VF.isScalar() || !TheLoop->contains(I))
7341 return TTI::CastContextHint::Normal;
7342
7343 switch (getWideningDecision(I, VF)) {
7344 case LoopVectorizationCostModel::CM_GatherScatter:
7345 return TTI::CastContextHint::GatherScatter;
7346 case LoopVectorizationCostModel::CM_Interleave:
7347 return TTI::CastContextHint::Interleave;
7348 case LoopVectorizationCostModel::CM_Scalarize:
7349 case LoopVectorizationCostModel::CM_Widen:
7350 return Legal->isMaskRequired(I) ? TTI::CastContextHint::Masked
7351 : TTI::CastContextHint::Normal;
7352 case LoopVectorizationCostModel::CM_Widen_Reverse:
7353 return TTI::CastContextHint::Reversed;
7354 case LoopVectorizationCostModel::CM_Unknown:
7355 llvm_unreachable("Instr did not go through cost modelling?")::llvm::llvm_unreachable_internal("Instr did not go through cost modelling?"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7355)
;
7356 }
7357
7358 llvm_unreachable("Unhandled case!")::llvm::llvm_unreachable_internal("Unhandled case!", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 7358)
;
7359 };
7360
7361 unsigned Opcode = I->getOpcode();
7362 TTI::CastContextHint CCH = TTI::CastContextHint::None;
7363 // For Trunc, the context is the only user, which must be a StoreInst.
7364 if (Opcode == Instruction::Trunc || Opcode == Instruction::FPTrunc) {
7365 if (I->hasOneUse())
7366 if (StoreInst *Store = dyn_cast<StoreInst>(*I->user_begin()))
7367 CCH = ComputeCCH(Store);
7368 }
7369 // For Z/Sext, the context is the operand, which must be a LoadInst.
7370 else if (Opcode == Instruction::ZExt || Opcode == Instruction::SExt ||
7371 Opcode == Instruction::FPExt) {
7372 if (LoadInst *Load = dyn_cast<LoadInst>(I->getOperand(0)))
7373 CCH = ComputeCCH(Load);
7374 }
7375
7376 // We optimize the truncation of induction variables having constant
7377 // integer steps. The cost of these truncations is the same as the scalar
7378 // operation.
7379 if (isOptimizableIVTruncate(I, VF)) {
7380 auto *Trunc = cast<TruncInst>(I);
7381 return TTI.getCastInstrCost(Instruction::Trunc, Trunc->getDestTy(),
7382 Trunc->getSrcTy(), CCH, CostKind, Trunc);
7383 }
7384
7385 // Detect reduction patterns
7386 if (auto RedCost = getReductionPatternCost(I, VF, VectorTy, CostKind))
7387 return *RedCost;
7388
7389 Type *SrcScalarTy = I->getOperand(0)->getType();
7390 Type *SrcVecTy =
7391 VectorTy->isVectorTy() ? ToVectorTy(SrcScalarTy, VF) : SrcScalarTy;
7392 if (canTruncateToMinimalBitwidth(I, VF)) {
7393 // This cast is going to be shrunk. This may remove the cast or it might
7394 // turn it into slightly different cast. For example, if MinBW == 16,
7395 // "zext i8 %1 to i32" becomes "zext i8 %1 to i16".
7396 //
7397 // Calculate the modified src and dest types.
7398 Type *MinVecTy = VectorTy;
7399 if (Opcode == Instruction::Trunc) {
7400 SrcVecTy = smallestIntegerVectorType(SrcVecTy, MinVecTy);
7401 VectorTy =
7402 largestIntegerVectorType(ToVectorTy(I->getType(), VF), MinVecTy);
7403 } else if (Opcode == Instruction::ZExt || Opcode == Instruction::SExt) {
7404 SrcVecTy = largestIntegerVectorType(SrcVecTy, MinVecTy);
7405 VectorTy =
7406 smallestIntegerVectorType(ToVectorTy(I->getType(), VF), MinVecTy);
7407 }
7408 }
7409
7410 return TTI.getCastInstrCost(Opcode, VectorTy, SrcVecTy, CCH, CostKind, I);
7411 }
7412 case Instruction::Call: {
7413 if (RecurrenceDescriptor::isFMulAddIntrinsic(I))
7414 if (auto RedCost = getReductionPatternCost(I, VF, VectorTy, CostKind))
7415 return *RedCost;
7416 bool NeedToScalarize;
7417 CallInst *CI = cast<CallInst>(I);
7418 InstructionCost CallCost = getVectorCallCost(CI, VF, NeedToScalarize);
7419 if (getVectorIntrinsicIDForCall(CI, TLI)) {
7420 InstructionCost IntrinsicCost = getVectorIntrinsicCost(CI, VF);
7421 return std::min(CallCost, IntrinsicCost);
7422 }
7423 return CallCost;
7424 }
7425 case Instruction::ExtractValue:
7426 return TTI.getInstructionCost(I, TTI::TCK_RecipThroughput);
7427 case Instruction::Alloca:
7428 // We cannot easily widen alloca to a scalable alloca, as
7429 // the result would need to be a vector of pointers.
7430 if (VF.isScalable())
7431 return InstructionCost::getInvalid();
7432 LLVM_FALLTHROUGH[[gnu::fallthrough]];
7433 default:
7434 // This opcode is unknown. Assume that it is the same as 'mul'.
7435 return TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy, CostKind);
7436 } // end of switch.
7437}
7438
7439char LoopVectorize::ID = 0;
7440
7441static const char lv_name[] = "Loop Vectorization";
7442
7443INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)static void *initializeLoopVectorizePassOnce(PassRegistry &
Registry) {
7444INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)initializeTargetTransformInfoWrapperPassPass(Registry);
7445INITIALIZE_PASS_DEPENDENCY(BasicAAWrapperPass)initializeBasicAAWrapperPassPass(Registry);
7446INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass)initializeAAResultsWrapperPassPass(Registry);
7447INITIALIZE_PASS_DEPENDENCY(GlobalsAAWrapperPass)initializeGlobalsAAWrapperPassPass(Registry);
7448INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)initializeAssumptionCacheTrackerPass(Registry);
7449INITIALIZE_PASS_DEPENDENCY(BlockFrequencyInfoWrapperPass)initializeBlockFrequencyInfoWrapperPassPass(Registry);
7450INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)initializeDominatorTreeWrapperPassPass(Registry);
7451INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass)initializeScalarEvolutionWrapperPassPass(Registry);
7452INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)initializeLoopInfoWrapperPassPass(Registry);
7453INITIALIZE_PASS_DEPENDENCY(LoopAccessLegacyAnalysis)initializeLoopAccessLegacyAnalysisPass(Registry);
7454INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass)initializeDemandedBitsWrapperPassPass(Registry);
7455INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass)initializeOptimizationRemarkEmitterWrapperPassPass(Registry);
7456INITIALIZE_PASS_DEPENDENCY(ProfileSummaryInfoWrapperPass)initializeProfileSummaryInfoWrapperPassPass(Registry);
7457INITIALIZE_PASS_DEPENDENCY(InjectTLIMappingsLegacy)initializeInjectTLIMappingsLegacyPass(Registry);
7458INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)PassInfo *PI = new PassInfo( lv_name, "loop-vectorize", &
LoopVectorize::ID, PassInfo::NormalCtor_t(callDefaultCtor<
LoopVectorize>), false, false); Registry.registerPass(*PI,
true); return PI; } static llvm::once_flag InitializeLoopVectorizePassFlag
; void llvm::initializeLoopVectorizePass(PassRegistry &Registry
) { llvm::call_once(InitializeLoopVectorizePassFlag, initializeLoopVectorizePassOnce
, std::ref(Registry)); }
7459
7460namespace llvm {
7461
7462Pass *createLoopVectorizePass() { return new LoopVectorize(); }
7463
7464Pass *createLoopVectorizePass(bool InterleaveOnlyWhenForced,
7465 bool VectorizeOnlyWhenForced) {
7466 return new LoopVectorize(InterleaveOnlyWhenForced, VectorizeOnlyWhenForced);
7467}
7468
7469} // end namespace llvm
7470
7471bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) {
7472 // Check if the pointer operand of a load or store instruction is
7473 // consecutive.
7474 if (auto *Ptr = getLoadStorePointerOperand(Inst))
7475 return Legal->isConsecutivePtr(getLoadStoreType(Inst), Ptr);
7476 return false;
7477}
7478
7479void LoopVectorizationCostModel::collectValuesToIgnore() {
7480 // Ignore ephemeral values.
7481 CodeMetrics::collectEphemeralValues(TheLoop, AC, ValuesToIgnore);
7482
7483 // Ignore type-promoting instructions we identified during reduction
7484 // detection.
7485 for (auto &Reduction : Legal->getReductionVars()) {
7486 const RecurrenceDescriptor &RedDes = Reduction.second;
7487 const SmallPtrSetImpl<Instruction *> &Casts = RedDes.getCastInsts();
7488 VecValuesToIgnore.insert(Casts.begin(), Casts.end());
7489 }
7490 // Ignore type-casting instructions we identified during induction
7491 // detection.
7492 for (auto &Induction : Legal->getInductionVars()) {
7493 const InductionDescriptor &IndDes = Induction.second;
7494 const SmallVectorImpl<Instruction *> &Casts = IndDes.getCastInsts();
7495 VecValuesToIgnore.insert(Casts.begin(), Casts.end());
7496 }
7497}
7498
7499void LoopVectorizationCostModel::collectInLoopReductions() {
7500 for (auto &Reduction : Legal->getReductionVars()) {
7501 PHINode *Phi = Reduction.first;
7502 const RecurrenceDescriptor &RdxDesc = Reduction.second;
7503
7504 // We don't collect reductions that are type promoted (yet).
7505 if (RdxDesc.getRecurrenceType() != Phi->getType())
7506 continue;
7507
7508 // If the target would prefer this reduction to happen "in-loop", then we
7509 // want to record it as such.
7510 unsigned Opcode = RdxDesc.getOpcode();
7511 if (!PreferInLoopReductions && !useOrderedReductions(RdxDesc) &&
7512 !TTI.preferInLoopReduction(Opcode, Phi->getType(),
7513 TargetTransformInfo::ReductionFlags()))
7514 continue;
7515
7516 // Check that we can correctly put the reductions into the loop, by
7517 // finding the chain of operations that leads from the phi to the loop
7518 // exit value.
7519 SmallVector<Instruction *, 4> ReductionOperations =
7520 RdxDesc.getReductionOpChain(Phi, TheLoop);
7521 bool InLoop = !ReductionOperations.empty();
7522 if (InLoop) {
7523 InLoopReductionChains[Phi] = ReductionOperations;
7524 // Add the elements to InLoopReductionImmediateChains for cost modelling.
7525 Instruction *LastChain = Phi;
7526 for (auto *I : ReductionOperations) {
7527 InLoopReductionImmediateChains[I] = LastChain;
7528 LastChain = I;
7529 }
7530 }
7531 LLVM_DEBUG(dbgs() << "LV: Using " << (InLoop ? "inloop" : "out of loop")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Using " << (
InLoop ? "inloop" : "out of loop") << " reduction for phi: "
<< *Phi << "\n"; } } while (false)
7532 << " reduction for phi: " << *Phi << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Using " << (
InLoop ? "inloop" : "out of loop") << " reduction for phi: "
<< *Phi << "\n"; } } while (false)
;
7533 }
7534}
7535
7536// TODO: we could return a pair of values that specify the max VF and
7537// min VF, to be used in `buildVPlans(MinVF, MaxVF)` instead of
7538// `buildVPlans(VF, VF)`. We cannot do it because VPLAN at the moment
7539// doesn't have a cost model that can choose which plan to execute if
7540// more than one is generated.
7541static unsigned determineVPlanVF(const unsigned WidestVectorRegBits,
7542 LoopVectorizationCostModel &CM) {
7543 unsigned WidestType;
7544 std::tie(std::ignore, WidestType) = CM.getSmallestAndWidestTypes();
7545 return WidestVectorRegBits / WidestType;
7546}
7547
7548VectorizationFactor
7549LoopVectorizationPlanner::planInVPlanNativePath(ElementCount UserVF) {
7550 assert(!UserVF.isScalable() && "scalable vectors not yet supported")(static_cast <bool> (!UserVF.isScalable() && "scalable vectors not yet supported"
) ? void (0) : __assert_fail ("!UserVF.isScalable() && \"scalable vectors not yet supported\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7550, __extension__
__PRETTY_FUNCTION__))
;
7551 ElementCount VF = UserVF;
7552 // Outer loop handling: They may require CFG and instruction level
7553 // transformations before even evaluating whether vectorization is profitable.
7554 // Since we cannot modify the incoming IR, we need to build VPlan upfront in
7555 // the vectorization pipeline.
7556 if (!OrigLoop->isInnermost()) {
7557 // If the user doesn't provide a vectorization factor, determine a
7558 // reasonable one.
7559 if (UserVF.isZero()) {
7560 VF = ElementCount::getFixed(determineVPlanVF(
7561 TTI->getRegisterBitWidth(TargetTransformInfo::RGK_FixedWidthVector)
7562 .getFixedSize(),
7563 CM));
7564 LLVM_DEBUG(dbgs() << "LV: VPlan computed VF " << VF << ".\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: VPlan computed VF "
<< VF << ".\n"; } } while (false)
;
7565
7566 // Make sure we have a VF > 1 for stress testing.
7567 if (VPlanBuildStressTest && (VF.isScalar() || VF.isZero())) {
7568 LLVM_DEBUG(dbgs() << "LV: VPlan stress testing: "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: VPlan stress testing: "
<< "overriding computed VF.\n"; } } while (false)
7569 << "overriding computed VF.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: VPlan stress testing: "
<< "overriding computed VF.\n"; } } while (false)
;
7570 VF = ElementCount::getFixed(4);
7571 }
7572 }
7573 assert(EnableVPlanNativePath && "VPlan-native path is not enabled.")(static_cast <bool> (EnableVPlanNativePath && "VPlan-native path is not enabled."
) ? void (0) : __assert_fail ("EnableVPlanNativePath && \"VPlan-native path is not enabled.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7573, __extension__
__PRETTY_FUNCTION__))
;
7574 assert(isPowerOf2_32(VF.getKnownMinValue()) &&(static_cast <bool> (isPowerOf2_32(VF.getKnownMinValue(
)) && "VF needs to be a power of two") ? void (0) : __assert_fail
("isPowerOf2_32(VF.getKnownMinValue()) && \"VF needs to be a power of two\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7575, __extension__
__PRETTY_FUNCTION__))
7575 "VF needs to be a power of two")(static_cast <bool> (isPowerOf2_32(VF.getKnownMinValue(
)) && "VF needs to be a power of two") ? void (0) : __assert_fail
("isPowerOf2_32(VF.getKnownMinValue()) && \"VF needs to be a power of two\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7575, __extension__
__PRETTY_FUNCTION__))
;
7576 LLVM_DEBUG(dbgs() << "LV: Using " << (!UserVF.isZero() ? "user " : "")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Using " << (
!UserVF.isZero() ? "user " : "") << "VF " << VF <<
" to build VPlans.\n"; } } while (false)
7577 << "VF " << VF << " to build VPlans.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Using " << (
!UserVF.isZero() ? "user " : "") << "VF " << VF <<
" to build VPlans.\n"; } } while (false)
;
7578 buildVPlans(VF, VF);
7579
7580 // For VPlan build stress testing, we bail out after VPlan construction.
7581 if (VPlanBuildStressTest)
7582 return VectorizationFactor::Disabled();
7583
7584 return {VF, 0 /*Cost*/};
7585 }
7586
7587 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not vectorizing. Inner loops aren't supported in the "
"VPlan-native path.\n"; } } while (false)
7588 dbgs() << "LV: Not vectorizing. Inner loops aren't supported in the "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not vectorizing. Inner loops aren't supported in the "
"VPlan-native path.\n"; } } while (false)
7589 "VPlan-native path.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not vectorizing. Inner loops aren't supported in the "
"VPlan-native path.\n"; } } while (false)
;
7590 return VectorizationFactor::Disabled();
7591}
7592
7593Optional<VectorizationFactor>
7594LoopVectorizationPlanner::plan(ElementCount UserVF, unsigned UserIC) {
7595 assert(OrigLoop->isInnermost() && "Inner loop expected.")(static_cast <bool> (OrigLoop->isInnermost() &&
"Inner loop expected.") ? void (0) : __assert_fail ("OrigLoop->isInnermost() && \"Inner loop expected.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7595, __extension__
__PRETTY_FUNCTION__))
;
7596 FixedScalableVFPair MaxFactors = CM.computeMaxVF(UserVF, UserIC);
7597 if (!MaxFactors) // Cases that should not to be vectorized nor interleaved.
7598 return None;
7599
7600 // Invalidate interleave groups if all blocks of loop will be predicated.
7601 if (CM.blockNeedsPredicationForAnyReason(OrigLoop->getHeader()) &&
7602 !useMaskedInterleavedAccesses(*TTI)) {
7603 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Invalidate all interleaved groups due to fold-tail by masking "
"which requires masked-interleaved support.\n"; } } while (false
)
7604 dbgs()do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Invalidate all interleaved groups due to fold-tail by masking "
"which requires masked-interleaved support.\n"; } } while (false
)
7605 << "LV: Invalidate all interleaved groups due to fold-tail by masking "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Invalidate all interleaved groups due to fold-tail by masking "
"which requires masked-interleaved support.\n"; } } while (false
)
7606 "which requires masked-interleaved support.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Invalidate all interleaved groups due to fold-tail by masking "
"which requires masked-interleaved support.\n"; } } while (false
)
;
7607 if (CM.InterleaveInfo.invalidateGroups())
7608 // Invalidating interleave groups also requires invalidating all decisions
7609 // based on them, which includes widening decisions and uniform and scalar
7610 // values.
7611 CM.invalidateCostModelingDecisions();
7612 }
7613
7614 ElementCount MaxUserVF =
7615 UserVF.isScalable() ? MaxFactors.ScalableVF : MaxFactors.FixedVF;
7616 bool UserVFIsLegal = ElementCount::isKnownLE(UserVF, MaxUserVF);
7617 if (!UserVF.isZero() && UserVFIsLegal) {
7618 assert(isPowerOf2_32(UserVF.getKnownMinValue()) &&(static_cast <bool> (isPowerOf2_32(UserVF.getKnownMinValue
()) && "VF needs to be a power of two") ? void (0) : __assert_fail
("isPowerOf2_32(UserVF.getKnownMinValue()) && \"VF needs to be a power of two\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7619, __extension__
__PRETTY_FUNCTION__))
7619 "VF needs to be a power of two")(static_cast <bool> (isPowerOf2_32(UserVF.getKnownMinValue
()) && "VF needs to be a power of two") ? void (0) : __assert_fail
("isPowerOf2_32(UserVF.getKnownMinValue()) && \"VF needs to be a power of two\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7619, __extension__
__PRETTY_FUNCTION__))
;
7620 // Collect the instructions (and their associated costs) that will be more
7621 // profitable to scalarize.
7622 if (CM.selectUserVectorizationFactor(UserVF)) {
7623 LLVM_DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Using user VF " <<
UserVF << ".\n"; } } while (false)
;
7624 CM.collectInLoopReductions();
7625 buildVPlansWithVPRecipes(UserVF, UserVF);
7626 LLVM_DEBUG(printPlans(dbgs()))do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { printPlans(dbgs()); } } while (false)
;
7627 return {{UserVF, 0}};
7628 } else
7629 reportVectorizationInfo("UserVF ignored because of invalid costs.",
7630 "InvalidCost", ORE, OrigLoop);
7631 }
7632
7633 // Populate the set of Vectorization Factor Candidates.
7634 ElementCountSet VFCandidates;
7635 for (auto VF = ElementCount::getFixed(1);
7636 ElementCount::isKnownLE(VF, MaxFactors.FixedVF); VF *= 2)
7637 VFCandidates.insert(VF);
7638 for (auto VF = ElementCount::getScalable(1);
7639 ElementCount::isKnownLE(VF, MaxFactors.ScalableVF); VF *= 2)
7640 VFCandidates.insert(VF);
7641
7642 for (const auto &VF : VFCandidates) {
7643 // Collect Uniform and Scalar instructions after vectorization with VF.
7644 CM.collectUniformsAndScalars(VF);
7645
7646 // Collect the instructions (and their associated costs) that will be more
7647 // profitable to scalarize.
7648 if (VF.isVector())
7649 CM.collectInstsToScalarize(VF);
7650 }
7651
7652 CM.collectInLoopReductions();
7653 buildVPlansWithVPRecipes(ElementCount::getFixed(1), MaxFactors.FixedVF);
7654 buildVPlansWithVPRecipes(ElementCount::getScalable(1), MaxFactors.ScalableVF);
7655
7656 LLVM_DEBUG(printPlans(dbgs()))do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { printPlans(dbgs()); } } while (false)
;
7657 if (!MaxFactors.hasVector())
7658 return VectorizationFactor::Disabled();
7659
7660 // Select the optimal vectorization factor.
7661 auto SelectedVF = CM.selectVectorizationFactor(VFCandidates);
7662
7663 // Check if it is profitable to vectorize with runtime checks.
7664 unsigned NumRuntimePointerChecks = Requirements.getNumRuntimePointerChecks();
7665 if (SelectedVF.Width.getKnownMinValue() > 1 && NumRuntimePointerChecks) {
7666 bool PragmaThresholdReached =
7667 NumRuntimePointerChecks > PragmaVectorizeMemoryCheckThreshold;
7668 bool ThresholdReached =
7669 NumRuntimePointerChecks > VectorizerParams::RuntimeMemoryCheckThreshold;
7670 if ((ThresholdReached && !Hints.allowReordering()) ||
7671 PragmaThresholdReached) {
7672 ORE->emit([&]() {
7673 return OptimizationRemarkAnalysisAliasing(
7674 DEBUG_TYPE"loop-vectorize", "CantReorderMemOps", OrigLoop->getStartLoc(),
7675 OrigLoop->getHeader())
7676 << "loop not vectorized: cannot prove it is safe to reorder "
7677 "memory operations";
7678 });
7679 LLVM_DEBUG(dbgs() << "LV: Too many memory checks needed.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Too many memory checks needed.\n"
; } } while (false)
;
7680 Hints.emitRemarkWithHints();
7681 return VectorizationFactor::Disabled();
7682 }
7683 }
7684 return SelectedVF;
7685}
7686
7687VPlan &LoopVectorizationPlanner::getBestPlanFor(ElementCount VF) const {
7688 assert(count_if(VPlans,(static_cast <bool> (count_if(VPlans, [VF](const VPlanPtr
&Plan) { return Plan->hasVF(VF); }) == 1 && "Best VF has not a single VPlan."
) ? void (0) : __assert_fail ("count_if(VPlans, [VF](const VPlanPtr &Plan) { return Plan->hasVF(VF); }) == 1 && \"Best VF has not a single VPlan.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7691, __extension__
__PRETTY_FUNCTION__))
7689 [VF](const VPlanPtr &Plan) { return Plan->hasVF(VF); }) ==(static_cast <bool> (count_if(VPlans, [VF](const VPlanPtr
&Plan) { return Plan->hasVF(VF); }) == 1 && "Best VF has not a single VPlan."
) ? void (0) : __assert_fail ("count_if(VPlans, [VF](const VPlanPtr &Plan) { return Plan->hasVF(VF); }) == 1 && \"Best VF has not a single VPlan.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7691, __extension__
__PRETTY_FUNCTION__))
7690 1 &&(static_cast <bool> (count_if(VPlans, [VF](const VPlanPtr
&Plan) { return Plan->hasVF(VF); }) == 1 && "Best VF has not a single VPlan."
) ? void (0) : __assert_fail ("count_if(VPlans, [VF](const VPlanPtr &Plan) { return Plan->hasVF(VF); }) == 1 && \"Best VF has not a single VPlan.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7691, __extension__
__PRETTY_FUNCTION__))
7691 "Best VF has not a single VPlan.")(static_cast <bool> (count_if(VPlans, [VF](const VPlanPtr
&Plan) { return Plan->hasVF(VF); }) == 1 && "Best VF has not a single VPlan."
) ? void (0) : __assert_fail ("count_if(VPlans, [VF](const VPlanPtr &Plan) { return Plan->hasVF(VF); }) == 1 && \"Best VF has not a single VPlan.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7691, __extension__
__PRETTY_FUNCTION__))
;
7692
7693 for (const VPlanPtr &Plan : VPlans) {
7694 if (Plan->hasVF(VF))
7695 return *Plan.get();
7696 }
7697 llvm_unreachable("No plan found!")::llvm::llvm_unreachable_internal("No plan found!", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 7697)
;
7698}
7699
7700static void AddRuntimeUnrollDisableMetaData(Loop *L) {
7701 SmallVector<Metadata *, 4> MDs;
7702 // Reserve first location for self reference to the LoopID metadata node.
7703 MDs.push_back(nullptr);
7704 bool IsUnrollMetadata = false;
7705 MDNode *LoopID = L->getLoopID();
7706 if (LoopID) {
7707 // First find existing loop unrolling disable metadata.
7708 for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
7709 auto *MD = dyn_cast<MDNode>(LoopID->getOperand(i));
7710 if (MD) {
7711 const auto *S = dyn_cast<MDString>(MD->getOperand(0));
7712 IsUnrollMetadata =
7713 S && S->getString().startswith("llvm.loop.unroll.disable");
7714 }
7715 MDs.push_back(LoopID->getOperand(i));
7716 }
7717 }
7718
7719 if (!IsUnrollMetadata) {
7720 // Add runtime unroll disable metadata.
7721 LLVMContext &Context = L->getHeader()->getContext();
7722 SmallVector<Metadata *, 1> DisableOperands;
7723 DisableOperands.push_back(
7724 MDString::get(Context, "llvm.loop.unroll.runtime.disable"));
7725 MDNode *DisableNode = MDNode::get(Context, DisableOperands);
7726 MDs.push_back(DisableNode);
7727 MDNode *NewLoopID = MDNode::get(Context, MDs);
7728 // Set operand 0 to refer to the loop id itself.
7729 NewLoopID->replaceOperandWith(0, NewLoopID);
7730 L->setLoopID(NewLoopID);
7731 }
7732}
7733
7734void LoopVectorizationPlanner::executePlan(ElementCount BestVF, unsigned BestUF,
7735 VPlan &BestVPlan,
7736 InnerLoopVectorizer &ILV,
7737 DominatorTree *DT) {
7738 LLVM_DEBUG(dbgs() << "Executing best plan with VF=" << BestVF << ", UF=" << BestUFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "Executing best plan with VF="
<< BestVF << ", UF=" << BestUF << '\n'
; } } while (false)
1
Assuming 'DebugFlag' is false
2
Loop condition is false. Exiting loop
7739 << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "Executing best plan with VF="
<< BestVF << ", UF=" << BestUF << '\n'
; } } while (false)
;
7740
7741 // Perform the actual loop transformation.
7742
7743 // 1. Create a new empty loop. Unlink the old loop and connect the new one.
7744 VPTransformState State{BestVF, BestUF, LI, DT, ILV.Builder, &ILV, &BestVPlan};
7745 Value *CanonicalIVStartValue;
7746 std::tie(State.CFG.PrevBB, CanonicalIVStartValue) =
7747 ILV.createVectorizedLoopSkeleton();
7748 ILV.collectPoisonGeneratingRecipes(State);
7749
7750 ILV.printDebugTracesAtStart();
7751
7752 //===------------------------------------------------===//
7753 //
7754 // Notice: any optimization or new instruction that go
7755 // into the code below should also be implemented in
7756 // the cost-model.
7757 //
7758 //===------------------------------------------------===//
7759
7760 // 2. Copy and widen instructions from the old loop into the new loop.
7761 BestVPlan.prepareToExecute(ILV.getOrCreateTripCount(nullptr),
7762 ILV.getOrCreateVectorTripCount(nullptr),
3
Passing null pointer value via 1st parameter 'L'
4
Calling 'InnerLoopVectorizer::getOrCreateVectorTripCount'
7763 CanonicalIVStartValue, State);
7764 BestVPlan.execute(&State);
7765
7766 // Keep all loop hints from the original loop on the vector loop (we'll
7767 // replace the vectorizer-specific hints below).
7768 MDNode *OrigLoopID = OrigLoop->getLoopID();
7769
7770 Optional<MDNode *> VectorizedLoopID =
7771 makeFollowupLoopID(OrigLoopID, {LLVMLoopVectorizeFollowupAll,
7772 LLVMLoopVectorizeFollowupVectorized});
7773
7774 Loop *L = LI->getLoopFor(State.CFG.PrevBB);
7775 if (VectorizedLoopID.hasValue())
7776 L->setLoopID(VectorizedLoopID.getValue());
7777 else {
7778 // Keep all loop hints from the original loop on the vector loop (we'll
7779 // replace the vectorizer-specific hints below).
7780 if (MDNode *LID = OrigLoop->getLoopID())
7781 L->setLoopID(LID);
7782
7783 LoopVectorizeHints Hints(L, true, *ORE);
7784 Hints.setAlreadyVectorized();
7785 }
7786 // Disable runtime unrolling when vectorizing the epilogue loop.
7787 if (CanonicalIVStartValue)
7788 AddRuntimeUnrollDisableMetaData(L);
7789
7790 // 3. Fix the vectorized code: take care of header phi's, live-outs,
7791 // predication, updating analyses.
7792 ILV.fixVectorizedLoop(State);
7793
7794 ILV.printDebugTracesAtEnd();
7795}
7796
7797#if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP)
7798void LoopVectorizationPlanner::printPlans(raw_ostream &O) {
7799 for (const auto &Plan : VPlans)
7800 if (PrintVPlansInDotFormat)
7801 Plan->printDOT(O);
7802 else
7803 Plan->print(O);
7804}
7805#endif
7806
7807void LoopVectorizationPlanner::collectTriviallyDeadInstructions(
7808 SmallPtrSetImpl<Instruction *> &DeadInstructions) {
7809
7810 // We create new control-flow for the vectorized loop, so the original exit
7811 // conditions will be dead after vectorization if it's only used by the
7812 // terminator
7813 SmallVector<BasicBlock*> ExitingBlocks;
7814 OrigLoop->getExitingBlocks(ExitingBlocks);
7815 for (auto *BB : ExitingBlocks) {
7816 auto *Cmp = dyn_cast<Instruction>(BB->getTerminator()->getOperand(0));
7817 if (!Cmp || !Cmp->hasOneUse())
7818 continue;
7819
7820 // TODO: we should introduce a getUniqueExitingBlocks on Loop
7821 if (!DeadInstructions.insert(Cmp).second)
7822 continue;
7823
7824 // The operands of the icmp is often a dead trunc, used by IndUpdate.
7825 // TODO: can recurse through operands in general
7826 for (Value *Op : Cmp->operands()) {
7827 if (isa<TruncInst>(Op) && Op->hasOneUse())
7828 DeadInstructions.insert(cast<Instruction>(Op));
7829 }
7830 }
7831
7832 // We create new "steps" for induction variable updates to which the original
7833 // induction variables map. An original update instruction will be dead if
7834 // all its users except the induction variable are dead.
7835 auto *Latch = OrigLoop->getLoopLatch();
7836 for (auto &Induction : Legal->getInductionVars()) {
7837 PHINode *Ind = Induction.first;
7838 auto *IndUpdate = cast<Instruction>(Ind->getIncomingValueForBlock(Latch));
7839
7840 // If the tail is to be folded by masking, the primary induction variable,
7841 // if exists, isn't dead: it will be used for masking. Don't kill it.
7842 if (CM.foldTailByMasking() && IndUpdate == Legal->getPrimaryInduction())
7843 continue;
7844
7845 if (llvm::all_of(IndUpdate->users(), [&](User *U) -> bool {
7846 return U == Ind || DeadInstructions.count(cast<Instruction>(U));
7847 }))
7848 DeadInstructions.insert(IndUpdate);
7849 }
7850}
7851
7852Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) { return V; }
7853
7854//===--------------------------------------------------------------------===//
7855// EpilogueVectorizerMainLoop
7856//===--------------------------------------------------------------------===//
7857
7858/// This function is partially responsible for generating the control flow
7859/// depicted in https://llvm.org/docs/Vectorizers.html#epilogue-vectorization.
7860std::pair<BasicBlock *, Value *>
7861EpilogueVectorizerMainLoop::createEpilogueVectorizedLoopSkeleton() {
7862 MDNode *OrigLoopID = OrigLoop->getLoopID();
7863 Loop *Lp = createVectorLoopSkeleton("");
7864
7865 // Generate the code to check the minimum iteration count of the vector
7866 // epilogue (see below).
7867 EPI.EpilogueIterationCountCheck =
7868 emitMinimumIterationCountCheck(Lp, LoopScalarPreHeader, true);
7869 EPI.EpilogueIterationCountCheck->setName("iter.check");
7870
7871 // Generate the code to check any assumptions that we've made for SCEV
7872 // expressions.
7873 EPI.SCEVSafetyCheck = emitSCEVChecks(LoopScalarPreHeader);
7874
7875 // Generate the code that checks at runtime if arrays overlap. We put the
7876 // checks into a separate block to make the more common case of few elements
7877 // faster.
7878 EPI.MemSafetyCheck = emitMemRuntimeChecks(Lp, LoopScalarPreHeader);
7879
7880 // Generate the iteration count check for the main loop, *after* the check
7881 // for the epilogue loop, so that the path-length is shorter for the case
7882 // that goes directly through the vector epilogue. The longer-path length for
7883 // the main loop is compensated for, by the gain from vectorizing the larger
7884 // trip count. Note: the branch will get updated later on when we vectorize
7885 // the epilogue.
7886 EPI.MainLoopIterationCountCheck =
7887 emitMinimumIterationCountCheck(Lp, LoopScalarPreHeader, false);
7888
7889 // Generate the induction variable.
7890 Value *CountRoundDown = getOrCreateVectorTripCount(Lp);
7891 EPI.VectorTripCount = CountRoundDown;
7892 createHeaderBranch(Lp);
7893
7894 // Skip induction resume value creation here because they will be created in
7895 // the second pass. If we created them here, they wouldn't be used anyway,
7896 // because the vplan in the second pass still contains the inductions from the
7897 // original loop.
7898
7899 return {completeLoopSkeleton(Lp, OrigLoopID), nullptr};
7900}
7901
7902void EpilogueVectorizerMainLoop::printDebugTracesAtStart() {
7903 LLVM_DEBUG({do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (first pass)\n"
<< "Main Loop VF:" << EPI.MainLoopVF << ", Main Loop UF:"
<< EPI.MainLoopUF << ", Epilogue Loop VF:" <<
EPI.EpilogueVF << ", Epilogue Loop UF:" << EPI.EpilogueUF
<< "\n"; }; } } while (false)
7904 dbgs() << "Create Skeleton for epilogue vectorized loop (first pass)\n"do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (first pass)\n"
<< "Main Loop VF:" << EPI.MainLoopVF << ", Main Loop UF:"
<< EPI.MainLoopUF << ", Epilogue Loop VF:" <<
EPI.EpilogueVF << ", Epilogue Loop UF:" << EPI.EpilogueUF
<< "\n"; }; } } while (false)
7905 << "Main Loop VF:" << EPI.MainLoopVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (first pass)\n"
<< "Main Loop VF:" << EPI.MainLoopVF << ", Main Loop UF:"
<< EPI.MainLoopUF << ", Epilogue Loop VF:" <<
EPI.EpilogueVF << ", Epilogue Loop UF:" << EPI.EpilogueUF
<< "\n"; }; } } while (false)
7906 << ", Main Loop UF:" << EPI.MainLoopUFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (first pass)\n"
<< "Main Loop VF:" << EPI.MainLoopVF << ", Main Loop UF:"
<< EPI.MainLoopUF << ", Epilogue Loop VF:" <<
EPI.EpilogueVF << ", Epilogue Loop UF:" << EPI.EpilogueUF
<< "\n"; }; } } while (false)
7907 << ", Epilogue Loop VF:" << EPI.EpilogueVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (first pass)\n"
<< "Main Loop VF:" << EPI.MainLoopVF << ", Main Loop UF:"
<< EPI.MainLoopUF << ", Epilogue Loop VF:" <<
EPI.EpilogueVF << ", Epilogue Loop UF:" << EPI.EpilogueUF
<< "\n"; }; } } while (false)
7908 << ", Epilogue Loop UF:" << EPI.EpilogueUF << "\n";do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (first pass)\n"
<< "Main Loop VF:" << EPI.MainLoopVF << ", Main Loop UF:"
<< EPI.MainLoopUF << ", Epilogue Loop VF:" <<
EPI.EpilogueVF << ", Epilogue Loop UF:" << EPI.EpilogueUF
<< "\n"; }; } } while (false)
7909 })do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (first pass)\n"
<< "Main Loop VF:" << EPI.MainLoopVF << ", Main Loop UF:"
<< EPI.MainLoopUF << ", Epilogue Loop VF:" <<
EPI.EpilogueVF << ", Epilogue Loop UF:" << EPI.EpilogueUF
<< "\n"; }; } } while (false)
;
7910}
7911
7912void EpilogueVectorizerMainLoop::printDebugTracesAtEnd() {
7913 DEBUG_WITH_TYPE(VerboseDebug, {do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
(VerboseDebug)) { { dbgs() << "intermediate fn:\n" <<
*OrigLoop->getHeader()->getParent() << "\n"; }; }
} while (false)
7914 dbgs() << "intermediate fn:\n"do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
(VerboseDebug)) { { dbgs() << "intermediate fn:\n" <<
*OrigLoop->getHeader()->getParent() << "\n"; }; }
} while (false)
7915 << *OrigLoop->getHeader()->getParent() << "\n";do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
(VerboseDebug)) { { dbgs() << "intermediate fn:\n" <<
*OrigLoop->getHeader()->getParent() << "\n"; }; }
} while (false)
7916 })do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
(VerboseDebug)) { { dbgs() << "intermediate fn:\n" <<
*OrigLoop->getHeader()->getParent() << "\n"; }; }
} while (false)
;
7917}
7918
7919BasicBlock *EpilogueVectorizerMainLoop::emitMinimumIterationCountCheck(
7920 Loop *L, BasicBlock *Bypass, bool ForEpilogue) {
7921 assert(L && "Expected valid Loop.")(static_cast <bool> (L && "Expected valid Loop."
) ? void (0) : __assert_fail ("L && \"Expected valid Loop.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7921, __extension__
__PRETTY_FUNCTION__))
;
7922 assert(Bypass && "Expected valid bypass basic block.")(static_cast <bool> (Bypass && "Expected valid bypass basic block."
) ? void (0) : __assert_fail ("Bypass && \"Expected valid bypass basic block.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7922, __extension__
__PRETTY_FUNCTION__))
;
7923 ElementCount VFactor = ForEpilogue ? EPI.EpilogueVF : VF;
7924 unsigned UFactor = ForEpilogue ? EPI.EpilogueUF : UF;
7925 Value *Count = getOrCreateTripCount(L);
7926 // Reuse existing vector loop preheader for TC checks.
7927 // Note that new preheader block is generated for vector loop.
7928 BasicBlock *const TCCheckBlock = LoopVectorPreHeader;
7929 IRBuilder<> Builder(TCCheckBlock->getTerminator());
7930
7931 // Generate code to check if the loop's trip count is less than VF * UF of the
7932 // main vector loop.
7933 auto P = Cost->requiresScalarEpilogue(ForEpilogue ? EPI.EpilogueVF : VF) ?
7934 ICmpInst::ICMP_ULE : ICmpInst::ICMP_ULT;
7935
7936 Value *CheckMinIters = Builder.CreateICmp(
7937 P, Count, createStepForVF(Builder, Count->getType(), VFactor, UFactor),
7938 "min.iters.check");
7939
7940 if (!ForEpilogue)
7941 TCCheckBlock->setName("vector.main.loop.iter.check");
7942
7943 // Create new preheader for vector loop.
7944 LoopVectorPreHeader = SplitBlock(TCCheckBlock, TCCheckBlock->getTerminator(),
7945 DT, LI, nullptr, "vector.ph");
7946
7947 if (ForEpilogue) {
7948 assert(DT->properlyDominates(DT->getNode(TCCheckBlock),(static_cast <bool> (DT->properlyDominates(DT->getNode
(TCCheckBlock), DT->getNode(Bypass)->getIDom()) &&
"TC check is expected to dominate Bypass") ? void (0) : __assert_fail
("DT->properlyDominates(DT->getNode(TCCheckBlock), DT->getNode(Bypass)->getIDom()) && \"TC check is expected to dominate Bypass\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7950, __extension__
__PRETTY_FUNCTION__))
7949 DT->getNode(Bypass)->getIDom()) &&(static_cast <bool> (DT->properlyDominates(DT->getNode
(TCCheckBlock), DT->getNode(Bypass)->getIDom()) &&
"TC check is expected to dominate Bypass") ? void (0) : __assert_fail
("DT->properlyDominates(DT->getNode(TCCheckBlock), DT->getNode(Bypass)->getIDom()) && \"TC check is expected to dominate Bypass\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7950, __extension__
__PRETTY_FUNCTION__))
7950 "TC check is expected to dominate Bypass")(static_cast <bool> (DT->properlyDominates(DT->getNode
(TCCheckBlock), DT->getNode(Bypass)->getIDom()) &&
"TC check is expected to dominate Bypass") ? void (0) : __assert_fail
("DT->properlyDominates(DT->getNode(TCCheckBlock), DT->getNode(Bypass)->getIDom()) && \"TC check is expected to dominate Bypass\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7950, __extension__
__PRETTY_FUNCTION__))
;
7951
7952 // Update dominator for Bypass & LoopExit.
7953 DT->changeImmediateDominator(Bypass, TCCheckBlock);
7954 if (!Cost->requiresScalarEpilogue(EPI.EpilogueVF))
7955 // For loops with multiple exits, there's no edge from the middle block
7956 // to exit blocks (as the epilogue must run) and thus no need to update
7957 // the immediate dominator of the exit blocks.
7958 DT->changeImmediateDominator(LoopExitBlock, TCCheckBlock);
7959
7960 LoopBypassBlocks.push_back(TCCheckBlock);
7961
7962 // Save the trip count so we don't have to regenerate it in the
7963 // vec.epilog.iter.check. This is safe to do because the trip count
7964 // generated here dominates the vector epilog iter check.
7965 EPI.TripCount = Count;
7966 }
7967
7968 ReplaceInstWithInst(
7969 TCCheckBlock->getTerminator(),
7970 BranchInst::Create(Bypass, LoopVectorPreHeader, CheckMinIters));
7971
7972 return TCCheckBlock;
7973}
7974
7975//===--------------------------------------------------------------------===//
7976// EpilogueVectorizerEpilogueLoop
7977//===--------------------------------------------------------------------===//
7978
7979/// This function is partially responsible for generating the control flow
7980/// depicted in https://llvm.org/docs/Vectorizers.html#epilogue-vectorization.
7981std::pair<BasicBlock *, Value *>
7982EpilogueVectorizerEpilogueLoop::createEpilogueVectorizedLoopSkeleton() {
7983 MDNode *OrigLoopID = OrigLoop->getLoopID();
7984 Loop *Lp = createVectorLoopSkeleton("vec.epilog.");
7985
7986 // Now, compare the remaining count and if there aren't enough iterations to
7987 // execute the vectorized epilogue skip to the scalar part.
7988 BasicBlock *VecEpilogueIterationCountCheck = LoopVectorPreHeader;
7989 VecEpilogueIterationCountCheck->setName("vec.epilog.iter.check");
7990 LoopVectorPreHeader =
7991 SplitBlock(LoopVectorPreHeader, LoopVectorPreHeader->getTerminator(), DT,
7992 LI, nullptr, "vec.epilog.ph");
7993 emitMinimumVectorEpilogueIterCountCheck(LoopScalarPreHeader,
7994 VecEpilogueIterationCountCheck);
7995
7996 // Adjust the control flow taking the state info from the main loop
7997 // vectorization into account.
7998 assert(EPI.MainLoopIterationCountCheck && EPI.EpilogueIterationCountCheck &&(static_cast <bool> (EPI.MainLoopIterationCountCheck &&
EPI.EpilogueIterationCountCheck && "expected this to be saved from the previous pass."
) ? void (0) : __assert_fail ("EPI.MainLoopIterationCountCheck && EPI.EpilogueIterationCountCheck && \"expected this to be saved from the previous pass.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7999, __extension__
__PRETTY_FUNCTION__))
7999 "expected this to be saved from the previous pass.")(static_cast <bool> (EPI.MainLoopIterationCountCheck &&
EPI.EpilogueIterationCountCheck && "expected this to be saved from the previous pass."
) ? void (0) : __assert_fail ("EPI.MainLoopIterationCountCheck && EPI.EpilogueIterationCountCheck && \"expected this to be saved from the previous pass.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 7999, __extension__
__PRETTY_FUNCTION__))
;
8000 EPI.MainLoopIterationCountCheck->getTerminator()->replaceUsesOfWith(
8001 VecEpilogueIterationCountCheck, LoopVectorPreHeader);
8002
8003 DT->changeImmediateDominator(LoopVectorPreHeader,
8004 EPI.MainLoopIterationCountCheck);
8005
8006 EPI.EpilogueIterationCountCheck->getTerminator()->replaceUsesOfWith(
8007 VecEpilogueIterationCountCheck, LoopScalarPreHeader);
8008
8009 if (EPI.SCEVSafetyCheck)
8010 EPI.SCEVSafetyCheck->getTerminator()->replaceUsesOfWith(
8011 VecEpilogueIterationCountCheck, LoopScalarPreHeader);
8012 if (EPI.MemSafetyCheck)
8013 EPI.MemSafetyCheck->getTerminator()->replaceUsesOfWith(
8014 VecEpilogueIterationCountCheck, LoopScalarPreHeader);
8015
8016 DT->changeImmediateDominator(
8017 VecEpilogueIterationCountCheck,
8018 VecEpilogueIterationCountCheck->getSinglePredecessor());
8019
8020 DT->changeImmediateDominator(LoopScalarPreHeader,
8021 EPI.EpilogueIterationCountCheck);
8022 if (!Cost->requiresScalarEpilogue(EPI.EpilogueVF))
8023 // If there is an epilogue which must run, there's no edge from the
8024 // middle block to exit blocks and thus no need to update the immediate
8025 // dominator of the exit blocks.
8026 DT->changeImmediateDominator(LoopExitBlock,
8027 EPI.EpilogueIterationCountCheck);
8028
8029 // Keep track of bypass blocks, as they feed start values to the induction
8030 // phis in the scalar loop preheader.
8031 if (EPI.SCEVSafetyCheck)
8032 LoopBypassBlocks.push_back(EPI.SCEVSafetyCheck);
8033 if (EPI.MemSafetyCheck)
8034 LoopBypassBlocks.push_back(EPI.MemSafetyCheck);
8035 LoopBypassBlocks.push_back(EPI.EpilogueIterationCountCheck);
8036
8037 // The vec.epilog.iter.check block may contain Phi nodes from reductions which
8038 // merge control-flow from the latch block and the middle block. Update the
8039 // incoming values here and move the Phi into the preheader.
8040 SmallVector<PHINode *, 4> PhisInBlock;
8041 for (PHINode &Phi : VecEpilogueIterationCountCheck->phis())
8042 PhisInBlock.push_back(&Phi);
8043
8044 for (PHINode *Phi : PhisInBlock) {
8045 Phi->replaceIncomingBlockWith(
8046 VecEpilogueIterationCountCheck->getSinglePredecessor(),
8047 VecEpilogueIterationCountCheck);
8048 Phi->removeIncomingValue(EPI.EpilogueIterationCountCheck);
8049 if (EPI.SCEVSafetyCheck)
8050 Phi->removeIncomingValue(EPI.SCEVSafetyCheck);
8051 if (EPI.MemSafetyCheck)
8052 Phi->removeIncomingValue(EPI.MemSafetyCheck);
8053 Phi->moveBefore(LoopVectorPreHeader->getFirstNonPHI());
8054 }
8055
8056 // Generate a resume induction for the vector epilogue and put it in the
8057 // vector epilogue preheader
8058 Type *IdxTy = Legal->getWidestInductionType();
8059 PHINode *EPResumeVal = PHINode::Create(IdxTy, 2, "vec.epilog.resume.val",
8060 LoopVectorPreHeader->getFirstNonPHI());
8061 EPResumeVal->addIncoming(EPI.VectorTripCount, VecEpilogueIterationCountCheck);
8062 EPResumeVal->addIncoming(ConstantInt::get(IdxTy, 0),
8063 EPI.MainLoopIterationCountCheck);
8064
8065 // Generate the induction variable.
8066 createHeaderBranch(Lp);
8067
8068 // Generate induction resume values. These variables save the new starting
8069 // indexes for the scalar loop. They are used to test if there are any tail
8070 // iterations left once the vector loop has completed.
8071 // Note that when the vectorized epilogue is skipped due to iteration count
8072 // check, then the resume value for the induction variable comes from
8073 // the trip count of the main vector loop, hence passing the AdditionalBypass
8074 // argument.
8075 createInductionResumeValues(Lp, {VecEpilogueIterationCountCheck,
8076 EPI.VectorTripCount} /* AdditionalBypass */);
8077
8078 return {completeLoopSkeleton(Lp, OrigLoopID), EPResumeVal};
8079}
8080
8081BasicBlock *
8082EpilogueVectorizerEpilogueLoop::emitMinimumVectorEpilogueIterCountCheck(
8083 BasicBlock *Bypass, BasicBlock *Insert) {
8084
8085 assert(EPI.TripCount &&(static_cast <bool> (EPI.TripCount && "Expected trip count to have been safed in the first pass."
) ? void (0) : __assert_fail ("EPI.TripCount && \"Expected trip count to have been safed in the first pass.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8086, __extension__
__PRETTY_FUNCTION__))
8086 "Expected trip count to have been safed in the first pass.")(static_cast <bool> (EPI.TripCount && "Expected trip count to have been safed in the first pass."
) ? void (0) : __assert_fail ("EPI.TripCount && \"Expected trip count to have been safed in the first pass.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8086, __extension__
__PRETTY_FUNCTION__))
;
8087 assert((static_cast <bool> ((!isa<Instruction>(EPI.TripCount
) || DT->dominates(cast<Instruction>(EPI.TripCount)->
getParent(), Insert)) && "saved trip count does not dominate insertion point."
) ? void (0) : __assert_fail ("(!isa<Instruction>(EPI.TripCount) || DT->dominates(cast<Instruction>(EPI.TripCount)->getParent(), Insert)) && \"saved trip count does not dominate insertion point.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8090, __extension__
__PRETTY_FUNCTION__))
8088 (!isa<Instruction>(EPI.TripCount) ||(static_cast <bool> ((!isa<Instruction>(EPI.TripCount
) || DT->dominates(cast<Instruction>(EPI.TripCount)->
getParent(), Insert)) && "saved trip count does not dominate insertion point."
) ? void (0) : __assert_fail ("(!isa<Instruction>(EPI.TripCount) || DT->dominates(cast<Instruction>(EPI.TripCount)->getParent(), Insert)) && \"saved trip count does not dominate insertion point.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8090, __extension__
__PRETTY_FUNCTION__))
8089 DT->dominates(cast<Instruction>(EPI.TripCount)->getParent(), Insert)) &&(static_cast <bool> ((!isa<Instruction>(EPI.TripCount
) || DT->dominates(cast<Instruction>(EPI.TripCount)->
getParent(), Insert)) && "saved trip count does not dominate insertion point."
) ? void (0) : __assert_fail ("(!isa<Instruction>(EPI.TripCount) || DT->dominates(cast<Instruction>(EPI.TripCount)->getParent(), Insert)) && \"saved trip count does not dominate insertion point.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8090, __extension__
__PRETTY_FUNCTION__))
8090 "saved trip count does not dominate insertion point.")(static_cast <bool> ((!isa<Instruction>(EPI.TripCount
) || DT->dominates(cast<Instruction>(EPI.TripCount)->
getParent(), Insert)) && "saved trip count does not dominate insertion point."
) ? void (0) : __assert_fail ("(!isa<Instruction>(EPI.TripCount) || DT->dominates(cast<Instruction>(EPI.TripCount)->getParent(), Insert)) && \"saved trip count does not dominate insertion point.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8090, __extension__
__PRETTY_FUNCTION__))
;
8091 Value *TC = EPI.TripCount;
8092 IRBuilder<> Builder(Insert->getTerminator());
8093 Value *Count = Builder.CreateSub(TC, EPI.VectorTripCount, "n.vec.remaining");
8094
8095 // Generate code to check if the loop's trip count is less than VF * UF of the
8096 // vector epilogue loop.
8097 auto P = Cost->requiresScalarEpilogue(EPI.EpilogueVF) ?
8098 ICmpInst::ICMP_ULE : ICmpInst::ICMP_ULT;
8099
8100 Value *CheckMinIters =
8101 Builder.CreateICmp(P, Count,
8102 createStepForVF(Builder, Count->getType(),
8103 EPI.EpilogueVF, EPI.EpilogueUF),
8104 "min.epilog.iters.check");
8105
8106 ReplaceInstWithInst(
8107 Insert->getTerminator(),
8108 BranchInst::Create(Bypass, LoopVectorPreHeader, CheckMinIters));
8109
8110 LoopBypassBlocks.push_back(Insert);
8111 return Insert;
8112}
8113
8114void EpilogueVectorizerEpilogueLoop::printDebugTracesAtStart() {
8115 LLVM_DEBUG({do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (second pass)\n"
<< "Epilogue Loop VF:" << EPI.EpilogueVF <<
", Epilogue Loop UF:" << EPI.EpilogueUF << "\n";
}; } } while (false)
8116 dbgs() << "Create Skeleton for epilogue vectorized loop (second pass)\n"do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (second pass)\n"
<< "Epilogue Loop VF:" << EPI.EpilogueVF <<
", Epilogue Loop UF:" << EPI.EpilogueUF << "\n";
}; } } while (false)
8117 << "Epilogue Loop VF:" << EPI.EpilogueVFdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (second pass)\n"
<< "Epilogue Loop VF:" << EPI.EpilogueVF <<
", Epilogue Loop UF:" << EPI.EpilogueUF << "\n";
}; } } while (false)
8118 << ", Epilogue Loop UF:" << EPI.EpilogueUF << "\n";do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (second pass)\n"
<< "Epilogue Loop VF:" << EPI.EpilogueVF <<
", Epilogue Loop UF:" << EPI.EpilogueUF << "\n";
}; } } while (false)
8119 })do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { { dbgs() << "Create Skeleton for epilogue vectorized loop (second pass)\n"
<< "Epilogue Loop VF:" << EPI.EpilogueVF <<
", Epilogue Loop UF:" << EPI.EpilogueUF << "\n";
}; } } while (false)
;
8120}
8121
8122void EpilogueVectorizerEpilogueLoop::printDebugTracesAtEnd() {
8123 DEBUG_WITH_TYPE(VerboseDebug, {do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
(VerboseDebug)) { { dbgs() << "final fn:\n" << *OrigLoop
->getHeader()->getParent() << "\n"; }; } } while (
false)
8124 dbgs() << "final fn:\n" << *OrigLoop->getHeader()->getParent() << "\n";do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
(VerboseDebug)) { { dbgs() << "final fn:\n" << *OrigLoop
->getHeader()->getParent() << "\n"; }; } } while (
false)
8125 })do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
(VerboseDebug)) { { dbgs() << "final fn:\n" << *OrigLoop
->getHeader()->getParent() << "\n"; }; } } while (
false)
;
8126}
8127
8128bool LoopVectorizationPlanner::getDecisionAndClampRange(
8129 const std::function<bool(ElementCount)> &Predicate, VFRange &Range) {
8130 assert(!Range.isEmpty() && "Trying to test an empty VF range.")(static_cast <bool> (!Range.isEmpty() && "Trying to test an empty VF range."
) ? void (0) : __assert_fail ("!Range.isEmpty() && \"Trying to test an empty VF range.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8130, __extension__
__PRETTY_FUNCTION__))
;
8131 bool PredicateAtRangeStart = Predicate(Range.Start);
8132
8133 for (ElementCount TmpVF = Range.Start * 2;
8134 ElementCount::isKnownLT(TmpVF, Range.End); TmpVF *= 2)
8135 if (Predicate(TmpVF) != PredicateAtRangeStart) {
8136 Range.End = TmpVF;
8137 break;
8138 }
8139
8140 return PredicateAtRangeStart;
8141}
8142
8143/// Build VPlans for the full range of feasible VF's = {\p MinVF, 2 * \p MinVF,
8144/// 4 * \p MinVF, ..., \p MaxVF} by repeatedly building a VPlan for a sub-range
8145/// of VF's starting at a given VF and extending it as much as possible. Each
8146/// vectorization decision can potentially shorten this sub-range during
8147/// buildVPlan().
8148void LoopVectorizationPlanner::buildVPlans(ElementCount MinVF,
8149 ElementCount MaxVF) {
8150 auto MaxVFPlusOne = MaxVF.getWithIncrement(1);
8151 for (ElementCount VF = MinVF; ElementCount::isKnownLT(VF, MaxVFPlusOne);) {
8152 VFRange SubRange = {VF, MaxVFPlusOne};
8153 VPlans.push_back(buildVPlan(SubRange));
8154 VF = SubRange.End;
8155 }
8156}
8157
8158VPValue *VPRecipeBuilder::createEdgeMask(BasicBlock *Src, BasicBlock *Dst,
8159 VPlanPtr &Plan) {
8160 assert(is_contained(predecessors(Dst), Src) && "Invalid edge")(static_cast <bool> (is_contained(predecessors(Dst), Src
) && "Invalid edge") ? void (0) : __assert_fail ("is_contained(predecessors(Dst), Src) && \"Invalid edge\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8160, __extension__
__PRETTY_FUNCTION__))
;
8161
8162 // Look for cached value.
8163 std::pair<BasicBlock *, BasicBlock *> Edge(Src, Dst);
8164 EdgeMaskCacheTy::iterator ECEntryIt = EdgeMaskCache.find(Edge);
8165 if (ECEntryIt != EdgeMaskCache.end())
8166 return ECEntryIt->second;
8167
8168 VPValue *SrcMask = createBlockInMask(Src, Plan);
8169
8170 // The terminator has to be a branch inst!
8171 BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
8172 assert(BI && "Unexpected terminator found")(static_cast <bool> (BI && "Unexpected terminator found"
) ? void (0) : __assert_fail ("BI && \"Unexpected terminator found\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8172, __extension__
__PRETTY_FUNCTION__))
;
8173
8174 if (!BI->isConditional() || BI->getSuccessor(0) == BI->getSuccessor(1))
8175 return EdgeMaskCache[Edge] = SrcMask;
8176
8177 // If source is an exiting block, we know the exit edge is dynamically dead
8178 // in the vector loop, and thus we don't need to restrict the mask. Avoid
8179 // adding uses of an otherwise potentially dead instruction.
8180 if (OrigLoop->isLoopExiting(Src))
8181 return EdgeMaskCache[Edge] = SrcMask;
8182
8183 VPValue *EdgeMask = Plan->getOrAddVPValue(BI->getCondition());
8184 assert(EdgeMask && "No Edge Mask found for condition")(static_cast <bool> (EdgeMask && "No Edge Mask found for condition"
) ? void (0) : __assert_fail ("EdgeMask && \"No Edge Mask found for condition\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8184, __extension__
__PRETTY_FUNCTION__))
;
8185
8186 if (BI->getSuccessor(0) != Dst)
8187 EdgeMask = Builder.createNot(EdgeMask, BI->getDebugLoc());
8188
8189 if (SrcMask) { // Otherwise block in-mask is all-one, no need to AND.
8190 // The condition is 'SrcMask && EdgeMask', which is equivalent to
8191 // 'select i1 SrcMask, i1 EdgeMask, i1 false'.
8192 // The select version does not introduce new UB if SrcMask is false and
8193 // EdgeMask is poison. Using 'and' here introduces undefined behavior.
8194 VPValue *False = Plan->getOrAddVPValue(
8195 ConstantInt::getFalse(BI->getCondition()->getType()));
8196 EdgeMask =
8197 Builder.createSelect(SrcMask, EdgeMask, False, BI->getDebugLoc());
8198 }
8199
8200 return EdgeMaskCache[Edge] = EdgeMask;
8201}
8202
8203VPValue *VPRecipeBuilder::createBlockInMask(BasicBlock *BB, VPlanPtr &Plan) {
8204 assert(OrigLoop->contains(BB) && "Block is not a part of a loop")(static_cast <bool> (OrigLoop->contains(BB) &&
"Block is not a part of a loop") ? void (0) : __assert_fail (
"OrigLoop->contains(BB) && \"Block is not a part of a loop\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8204, __extension__
__PRETTY_FUNCTION__))
;
8205
8206 // Look for cached value.
8207 BlockMaskCacheTy::iterator BCEntryIt = BlockMaskCache.find(BB);
8208 if (BCEntryIt != BlockMaskCache.end())
8209 return BCEntryIt->second;
8210
8211 // All-one mask is modelled as no-mask following the convention for masked
8212 // load/store/gather/scatter. Initialize BlockMask to no-mask.
8213 VPValue *BlockMask = nullptr;
8214
8215 if (OrigLoop->getHeader() == BB) {
8216 if (!CM.blockNeedsPredicationForAnyReason(BB))
8217 return BlockMaskCache[BB] = BlockMask; // Loop incoming mask is all-one.
8218
8219 // Introduce the early-exit compare IV <= BTC to form header block mask.
8220 // This is used instead of IV < TC because TC may wrap, unlike BTC. Start by
8221 // constructing the desired canonical IV in the header block as its first
8222 // non-phi instructions.
8223 assert(CM.foldTailByMasking() && "must fold the tail")(static_cast <bool> (CM.foldTailByMasking() && "must fold the tail"
) ? void (0) : __assert_fail ("CM.foldTailByMasking() && \"must fold the tail\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8223, __extension__
__PRETTY_FUNCTION__))
;
8224 VPBasicBlock *HeaderVPBB = Plan->getEntry()->getEntryBasicBlock();
8225 auto NewInsertionPoint = HeaderVPBB->getFirstNonPhi();
8226 auto *IV = new VPWidenCanonicalIVRecipe(Plan->getCanonicalIV());
8227 HeaderVPBB->insert(IV, HeaderVPBB->getFirstNonPhi());
8228
8229 VPBuilder::InsertPointGuard Guard(Builder);
8230 Builder.setInsertPoint(HeaderVPBB, NewInsertionPoint);
8231 if (CM.TTI.emitGetActiveLaneMask()) {
8232 VPValue *TC = Plan->getOrCreateTripCount();
8233 BlockMask = Builder.createNaryOp(VPInstruction::ActiveLaneMask, {IV, TC});
8234 } else {
8235 VPValue *BTC = Plan->getOrCreateBackedgeTakenCount();
8236 BlockMask = Builder.createNaryOp(VPInstruction::ICmpULE, {IV, BTC});
8237 }
8238 return BlockMaskCache[BB] = BlockMask;
8239 }
8240
8241 // This is the block mask. We OR all incoming edges.
8242 for (auto *Predecessor : predecessors(BB)) {
8243 VPValue *EdgeMask = createEdgeMask(Predecessor, BB, Plan);
8244 if (!EdgeMask) // Mask of predecessor is all-one so mask of block is too.
8245 return BlockMaskCache[BB] = EdgeMask;
8246
8247 if (!BlockMask) { // BlockMask has its initialized nullptr value.
8248 BlockMask = EdgeMask;
8249 continue;
8250 }
8251
8252 BlockMask = Builder.createOr(BlockMask, EdgeMask, {});
8253 }
8254
8255 return BlockMaskCache[BB] = BlockMask;
8256}
8257
8258VPRecipeBase *VPRecipeBuilder::tryToWidenMemory(Instruction *I,
8259 ArrayRef<VPValue *> Operands,
8260 VFRange &Range,
8261 VPlanPtr &Plan) {
8262 assert((isa<LoadInst>(I) || isa<StoreInst>(I)) &&(static_cast <bool> ((isa<LoadInst>(I) || isa<
StoreInst>(I)) && "Must be called with either a load or store"
) ? void (0) : __assert_fail ("(isa<LoadInst>(I) || isa<StoreInst>(I)) && \"Must be called with either a load or store\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8263, __extension__
__PRETTY_FUNCTION__))
8263 "Must be called with either a load or store")(static_cast <bool> ((isa<LoadInst>(I) || isa<
StoreInst>(I)) && "Must be called with either a load or store"
) ? void (0) : __assert_fail ("(isa<LoadInst>(I) || isa<StoreInst>(I)) && \"Must be called with either a load or store\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8263, __extension__
__PRETTY_FUNCTION__))
;
8264
8265 auto willWiden = [&](ElementCount VF) -> bool {
8266 if (VF.isScalar())
8267 return false;
8268 LoopVectorizationCostModel::InstWidening Decision =
8269 CM.getWideningDecision(I, VF);
8270 assert(Decision != LoopVectorizationCostModel::CM_Unknown &&(static_cast <bool> (Decision != LoopVectorizationCostModel
::CM_Unknown && "CM decision should be taken at this point."
) ? void (0) : __assert_fail ("Decision != LoopVectorizationCostModel::CM_Unknown && \"CM decision should be taken at this point.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8271, __extension__
__PRETTY_FUNCTION__))
8271 "CM decision should be taken at this point.")(static_cast <bool> (Decision != LoopVectorizationCostModel
::CM_Unknown && "CM decision should be taken at this point."
) ? void (0) : __assert_fail ("Decision != LoopVectorizationCostModel::CM_Unknown && \"CM decision should be taken at this point.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8271, __extension__
__PRETTY_FUNCTION__))
;
8272 if (Decision == LoopVectorizationCostModel::CM_Interleave)
8273 return true;
8274 if (CM.isScalarAfterVectorization(I, VF) ||
8275 CM.isProfitableToScalarize(I, VF))
8276 return false;
8277 return Decision != LoopVectorizationCostModel::CM_Scalarize;
8278 };
8279
8280 if (!LoopVectorizationPlanner::getDecisionAndClampRange(willWiden, Range))
8281 return nullptr;
8282
8283 VPValue *Mask = nullptr;
8284 if (Legal->isMaskRequired(I))
8285 Mask = createBlockInMask(I->getParent(), Plan);
8286
8287 // Determine if the pointer operand of the access is either consecutive or
8288 // reverse consecutive.
8289 LoopVectorizationCostModel::InstWidening Decision =
8290 CM.getWideningDecision(I, Range.Start);
8291 bool Reverse = Decision == LoopVectorizationCostModel::CM_Widen_Reverse;
8292 bool Consecutive =
8293 Reverse || Decision == LoopVectorizationCostModel::CM_Widen;
8294
8295 if (LoadInst *Load = dyn_cast<LoadInst>(I))
8296 return new VPWidenMemoryInstructionRecipe(*Load, Operands[0], Mask,
8297 Consecutive, Reverse);
8298
8299 StoreInst *Store = cast<StoreInst>(I);
8300 return new VPWidenMemoryInstructionRecipe(*Store, Operands[1], Operands[0],
8301 Mask, Consecutive, Reverse);
8302}
8303
8304static VPWidenIntOrFpInductionRecipe *
8305createWidenInductionRecipe(PHINode *Phi, Instruction *PhiOrTrunc,
8306 VPValue *Start, const InductionDescriptor &IndDesc,
8307 LoopVectorizationCostModel &CM, ScalarEvolution &SE,
8308 Loop &OrigLoop, VFRange &Range) {
8309 // Returns true if an instruction \p I should be scalarized instead of
8310 // vectorized for the chosen vectorization factor.
8311 auto ShouldScalarizeInstruction = [&CM](Instruction *I, ElementCount VF) {
8312 return CM.isScalarAfterVectorization(I, VF) ||
8313 CM.isProfitableToScalarize(I, VF);
8314 };
8315
8316 bool NeedsScalarIV = LoopVectorizationPlanner::getDecisionAndClampRange(
8317 [&](ElementCount VF) {
8318 // Returns true if we should generate a scalar version of \p IV.
8319 if (ShouldScalarizeInstruction(PhiOrTrunc, VF))
8320 return true;
8321 auto isScalarInst = [&](User *U) -> bool {
8322 auto *I = cast<Instruction>(U);
8323 return OrigLoop.contains(I) && ShouldScalarizeInstruction(I, VF);
8324 };
8325 return any_of(PhiOrTrunc->users(), isScalarInst);
8326 },
8327 Range);
8328 bool NeedsScalarIVOnly = LoopVectorizationPlanner::getDecisionAndClampRange(
8329 [&](ElementCount VF) {
8330 return ShouldScalarizeInstruction(PhiOrTrunc, VF);
8331 },
8332 Range);
8333 assert(IndDesc.getStartValue() ==(static_cast <bool> (IndDesc.getStartValue() == Phi->
getIncomingValueForBlock(OrigLoop.getLoopPreheader())) ? void
(0) : __assert_fail ("IndDesc.getStartValue() == Phi->getIncomingValueForBlock(OrigLoop.getLoopPreheader())"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8334, __extension__
__PRETTY_FUNCTION__))
8334 Phi->getIncomingValueForBlock(OrigLoop.getLoopPreheader()))(static_cast <bool> (IndDesc.getStartValue() == Phi->
getIncomingValueForBlock(OrigLoop.getLoopPreheader())) ? void
(0) : __assert_fail ("IndDesc.getStartValue() == Phi->getIncomingValueForBlock(OrigLoop.getLoopPreheader())"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8334, __extension__
__PRETTY_FUNCTION__))
;
8335 assert(SE.isLoopInvariant(IndDesc.getStep(), &OrigLoop) &&(static_cast <bool> (SE.isLoopInvariant(IndDesc.getStep
(), &OrigLoop) && "step must be loop invariant") ?
void (0) : __assert_fail ("SE.isLoopInvariant(IndDesc.getStep(), &OrigLoop) && \"step must be loop invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8336, __extension__
__PRETTY_FUNCTION__))
8336 "step must be loop invariant")(static_cast <bool> (SE.isLoopInvariant(IndDesc.getStep
(), &OrigLoop) && "step must be loop invariant") ?
void (0) : __assert_fail ("SE.isLoopInvariant(IndDesc.getStep(), &OrigLoop) && \"step must be loop invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8336, __extension__
__PRETTY_FUNCTION__))
;
8337 if (auto *TruncI = dyn_cast<TruncInst>(PhiOrTrunc)) {
8338 return new VPWidenIntOrFpInductionRecipe(
8339 Phi, Start, IndDesc, TruncI, NeedsScalarIV, !NeedsScalarIVOnly, SE);
8340 }
8341 assert(isa<PHINode>(PhiOrTrunc) && "must be a phi node here")(static_cast <bool> (isa<PHINode>(PhiOrTrunc) &&
"must be a phi node here") ? void (0) : __assert_fail ("isa<PHINode>(PhiOrTrunc) && \"must be a phi node here\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8341, __extension__
__PRETTY_FUNCTION__))
;
8342 return new VPWidenIntOrFpInductionRecipe(Phi, Start, IndDesc, NeedsScalarIV,
8343 !NeedsScalarIVOnly, SE);
8344}
8345
8346VPWidenIntOrFpInductionRecipe *VPRecipeBuilder::tryToOptimizeInductionPHI(
8347 PHINode *Phi, ArrayRef<VPValue *> Operands, VFRange &Range) const {
8348
8349 // Check if this is an integer or fp induction. If so, build the recipe that
8350 // produces its scalar and vector values.
8351 if (auto *II = Legal->getIntOrFpInductionDescriptor(Phi))
8352 return createWidenInductionRecipe(Phi, Phi, Operands[0], *II, CM,
8353 *PSE.getSE(), *OrigLoop, Range);
8354
8355 return nullptr;
8356}
8357
8358VPWidenIntOrFpInductionRecipe *VPRecipeBuilder::tryToOptimizeInductionTruncate(
8359 TruncInst *I, ArrayRef<VPValue *> Operands, VFRange &Range,
8360 VPlan &Plan) const {
8361 // Optimize the special case where the source is a constant integer
8362 // induction variable. Notice that we can only optimize the 'trunc' case
8363 // because (a) FP conversions lose precision, (b) sext/zext may wrap, and
8364 // (c) other casts depend on pointer size.
8365
8366 // Determine whether \p K is a truncation based on an induction variable that
8367 // can be optimized.
8368 auto isOptimizableIVTruncate =
8369 [&](Instruction *K) -> std::function<bool(ElementCount)> {
8370 return [=](ElementCount VF) -> bool {
8371 return CM.isOptimizableIVTruncate(K, VF);
8372 };
8373 };
8374
8375 if (LoopVectorizationPlanner::getDecisionAndClampRange(
8376 isOptimizableIVTruncate(I), Range)) {
8377
8378 auto *Phi = cast<PHINode>(I->getOperand(0));
8379 const InductionDescriptor &II = *Legal->getIntOrFpInductionDescriptor(Phi);
8380 VPValue *Start = Plan.getOrAddVPValue(II.getStartValue());
8381 return createWidenInductionRecipe(Phi, I, Start, II, CM, *PSE.getSE(),
8382 *OrigLoop, Range);
8383 }
8384 return nullptr;
8385}
8386
8387VPRecipeOrVPValueTy VPRecipeBuilder::tryToBlend(PHINode *Phi,
8388 ArrayRef<VPValue *> Operands,
8389 VPlanPtr &Plan) {
8390 // If all incoming values are equal, the incoming VPValue can be used directly
8391 // instead of creating a new VPBlendRecipe.
8392 VPValue *FirstIncoming = Operands[0];
8393 if (all_of(Operands, [FirstIncoming](const VPValue *Inc) {
8394 return FirstIncoming == Inc;
8395 })) {
8396 return Operands[0];
8397 }
8398
8399 unsigned NumIncoming = Phi->getNumIncomingValues();
8400 // For in-loop reductions, we do not need to create an additional select.
8401 VPValue *InLoopVal = nullptr;
8402 for (unsigned In = 0; In < NumIncoming; In++) {
8403 PHINode *PhiOp =
8404 dyn_cast_or_null<PHINode>(Operands[In]->getUnderlyingValue());
8405 if (PhiOp && CM.isInLoopReduction(PhiOp)) {
8406 assert(!InLoopVal && "Found more than one in-loop reduction!")(static_cast <bool> (!InLoopVal && "Found more than one in-loop reduction!"
) ? void (0) : __assert_fail ("!InLoopVal && \"Found more than one in-loop reduction!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8406, __extension__
__PRETTY_FUNCTION__))
;
8407 InLoopVal = Operands[In];
8408 }
8409 }
8410
8411 assert((!InLoopVal || NumIncoming == 2) &&(static_cast <bool> ((!InLoopVal || NumIncoming == 2) &&
"Found an in-loop reduction for PHI with unexpected number of "
"incoming values") ? void (0) : __assert_fail ("(!InLoopVal || NumIncoming == 2) && \"Found an in-loop reduction for PHI with unexpected number of \" \"incoming values\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8413, __extension__
__PRETTY_FUNCTION__))
8412 "Found an in-loop reduction for PHI with unexpected number of "(static_cast <bool> ((!InLoopVal || NumIncoming == 2) &&
"Found an in-loop reduction for PHI with unexpected number of "
"incoming values") ? void (0) : __assert_fail ("(!InLoopVal || NumIncoming == 2) && \"Found an in-loop reduction for PHI with unexpected number of \" \"incoming values\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8413, __extension__
__PRETTY_FUNCTION__))
8413 "incoming values")(static_cast <bool> ((!InLoopVal || NumIncoming == 2) &&
"Found an in-loop reduction for PHI with unexpected number of "
"incoming values") ? void (0) : __assert_fail ("(!InLoopVal || NumIncoming == 2) && \"Found an in-loop reduction for PHI with unexpected number of \" \"incoming values\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8413, __extension__
__PRETTY_FUNCTION__))
;
8414 if (InLoopVal)
8415 return Operands[Operands[0] == InLoopVal ? 1 : 0];
8416
8417 // We know that all PHIs in non-header blocks are converted into selects, so
8418 // we don't have to worry about the insertion order and we can just use the
8419 // builder. At this point we generate the predication tree. There may be
8420 // duplications since this is a simple recursive scan, but future
8421 // optimizations will clean it up.
8422 SmallVector<VPValue *, 2> OperandsWithMask;
8423
8424 for (unsigned In = 0; In < NumIncoming; In++) {
8425 VPValue *EdgeMask =
8426 createEdgeMask(Phi->getIncomingBlock(In), Phi->getParent(), Plan);
8427 assert((EdgeMask || NumIncoming == 1) &&(static_cast <bool> ((EdgeMask || NumIncoming == 1) &&
"Multiple predecessors with one having a full mask") ? void (
0) : __assert_fail ("(EdgeMask || NumIncoming == 1) && \"Multiple predecessors with one having a full mask\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8428, __extension__
__PRETTY_FUNCTION__))
8428 "Multiple predecessors with one having a full mask")(static_cast <bool> ((EdgeMask || NumIncoming == 1) &&
"Multiple predecessors with one having a full mask") ? void (
0) : __assert_fail ("(EdgeMask || NumIncoming == 1) && \"Multiple predecessors with one having a full mask\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8428, __extension__
__PRETTY_FUNCTION__))
;
8429 OperandsWithMask.push_back(Operands[In]);
8430 if (EdgeMask)
8431 OperandsWithMask.push_back(EdgeMask);
8432 }
8433 return toVPRecipeResult(new VPBlendRecipe(Phi, OperandsWithMask));
8434}
8435
8436VPWidenCallRecipe *VPRecipeBuilder::tryToWidenCall(CallInst *CI,
8437 ArrayRef<VPValue *> Operands,
8438 VFRange &Range) const {
8439
8440 bool IsPredicated = LoopVectorizationPlanner::getDecisionAndClampRange(
8441 [this, CI](ElementCount VF) {
8442 return CM.isScalarWithPredication(CI, VF);
8443 },
8444 Range);
8445
8446 if (IsPredicated)
8447 return nullptr;
8448
8449 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
8450 if (ID && (ID == Intrinsic::assume || ID == Intrinsic::lifetime_end ||
8451 ID == Intrinsic::lifetime_start || ID == Intrinsic::sideeffect ||
8452 ID == Intrinsic::pseudoprobe ||
8453 ID == Intrinsic::experimental_noalias_scope_decl))
8454 return nullptr;
8455
8456 auto willWiden = [&](ElementCount VF) -> bool {
8457 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
8458 // The following case may be scalarized depending on the VF.
8459 // The flag shows whether we use Intrinsic or a usual Call for vectorized
8460 // version of the instruction.
8461 // Is it beneficial to perform intrinsic call compared to lib call?
8462 bool NeedToScalarize = false;
8463 InstructionCost CallCost = CM.getVectorCallCost(CI, VF, NeedToScalarize);
8464 InstructionCost IntrinsicCost = ID ? CM.getVectorIntrinsicCost(CI, VF) : 0;
8465 bool UseVectorIntrinsic = ID && IntrinsicCost <= CallCost;
8466 return UseVectorIntrinsic || !NeedToScalarize;
8467 };
8468
8469 if (!LoopVectorizationPlanner::getDecisionAndClampRange(willWiden, Range))
8470 return nullptr;
8471
8472 ArrayRef<VPValue *> Ops = Operands.take_front(CI->arg_size());
8473 return new VPWidenCallRecipe(*CI, make_range(Ops.begin(), Ops.end()));
8474}
8475
8476bool VPRecipeBuilder::shouldWiden(Instruction *I, VFRange &Range) const {
8477 assert(!isa<BranchInst>(I) && !isa<PHINode>(I) && !isa<LoadInst>(I) &&(static_cast <bool> (!isa<BranchInst>(I) &&
!isa<PHINode>(I) && !isa<LoadInst>(I) &&
!isa<StoreInst>(I) && "Instruction should have been handled earlier"
) ? void (0) : __assert_fail ("!isa<BranchInst>(I) && !isa<PHINode>(I) && !isa<LoadInst>(I) && !isa<StoreInst>(I) && \"Instruction should have been handled earlier\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8478, __extension__
__PRETTY_FUNCTION__))
8478 !isa<StoreInst>(I) && "Instruction should have been handled earlier")(static_cast <bool> (!isa<BranchInst>(I) &&
!isa<PHINode>(I) && !isa<LoadInst>(I) &&
!isa<StoreInst>(I) && "Instruction should have been handled earlier"
) ? void (0) : __assert_fail ("!isa<BranchInst>(I) && !isa<PHINode>(I) && !isa<LoadInst>(I) && !isa<StoreInst>(I) && \"Instruction should have been handled earlier\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8478, __extension__
__PRETTY_FUNCTION__))
;
8479 // Instruction should be widened, unless it is scalar after vectorization,
8480 // scalarization is profitable or it is predicated.
8481 auto WillScalarize = [this, I](ElementCount VF) -> bool {
8482 return CM.isScalarAfterVectorization(I, VF) ||
8483 CM.isProfitableToScalarize(I, VF) ||
8484 CM.isScalarWithPredication(I, VF);
8485 };
8486 return !LoopVectorizationPlanner::getDecisionAndClampRange(WillScalarize,
8487 Range);
8488}
8489
8490VPWidenRecipe *VPRecipeBuilder::tryToWiden(Instruction *I,
8491 ArrayRef<VPValue *> Operands) const {
8492 auto IsVectorizableOpcode = [](unsigned Opcode) {
8493 switch (Opcode) {
8494 case Instruction::Add:
8495 case Instruction::And:
8496 case Instruction::AShr:
8497 case Instruction::BitCast:
8498 case Instruction::FAdd:
8499 case Instruction::FCmp:
8500 case Instruction::FDiv:
8501 case Instruction::FMul:
8502 case Instruction::FNeg:
8503 case Instruction::FPExt:
8504 case Instruction::FPToSI:
8505 case Instruction::FPToUI:
8506 case Instruction::FPTrunc:
8507 case Instruction::FRem:
8508 case Instruction::FSub:
8509 case Instruction::ICmp:
8510 case Instruction::IntToPtr:
8511 case Instruction::LShr:
8512 case Instruction::Mul:
8513 case Instruction::Or:
8514 case Instruction::PtrToInt:
8515 case Instruction::SDiv:
8516 case Instruction::Select:
8517 case Instruction::SExt:
8518 case Instruction::Shl:
8519 case Instruction::SIToFP:
8520 case Instruction::SRem:
8521 case Instruction::Sub:
8522 case Instruction::Trunc:
8523 case Instruction::UDiv:
8524 case Instruction::UIToFP:
8525 case Instruction::URem:
8526 case Instruction::Xor:
8527 case Instruction::ZExt:
8528 return true;
8529 }
8530 return false;
8531 };
8532
8533 if (!IsVectorizableOpcode(I->getOpcode()))
8534 return nullptr;
8535
8536 // Success: widen this instruction.
8537 return new VPWidenRecipe(*I, make_range(Operands.begin(), Operands.end()));
8538}
8539
8540void VPRecipeBuilder::fixHeaderPhis() {
8541 BasicBlock *OrigLatch = OrigLoop->getLoopLatch();
8542 for (VPHeaderPHIRecipe *R : PhisToFix) {
8543 auto *PN = cast<PHINode>(R->getUnderlyingValue());
8544 VPRecipeBase *IncR =
8545 getRecipe(cast<Instruction>(PN->getIncomingValueForBlock(OrigLatch)));
8546 R->addOperand(IncR->getVPSingleValue());
8547 }
8548}
8549
8550VPBasicBlock *VPRecipeBuilder::handleReplication(
8551 Instruction *I, VFRange &Range, VPBasicBlock *VPBB,
8552 VPlanPtr &Plan) {
8553 bool IsUniform = LoopVectorizationPlanner::getDecisionAndClampRange(
8554 [&](ElementCount VF) { return CM.isUniformAfterVectorization(I, VF); },
8555 Range);
8556
8557 bool IsPredicated = LoopVectorizationPlanner::getDecisionAndClampRange(
8558 [&](ElementCount VF) { return CM.isPredicatedInst(I, VF, IsUniform); },
8559 Range);
8560
8561 // Even if the instruction is not marked as uniform, there are certain
8562 // intrinsic calls that can be effectively treated as such, so we check for
8563 // them here. Conservatively, we only do this for scalable vectors, since
8564 // for fixed-width VFs we can always fall back on full scalarization.
8565 if (!IsUniform && Range.Start.isScalable() && isa<IntrinsicInst>(I)) {
8566 switch (cast<IntrinsicInst>(I)->getIntrinsicID()) {
8567 case Intrinsic::assume:
8568 case Intrinsic::lifetime_start:
8569 case Intrinsic::lifetime_end:
8570 // For scalable vectors if one of the operands is variant then we still
8571 // want to mark as uniform, which will generate one instruction for just
8572 // the first lane of the vector. We can't scalarize the call in the same
8573 // way as for fixed-width vectors because we don't know how many lanes
8574 // there are.
8575 //
8576 // The reasons for doing it this way for scalable vectors are:
8577 // 1. For the assume intrinsic generating the instruction for the first
8578 // lane is still be better than not generating any at all. For
8579 // example, the input may be a splat across all lanes.
8580 // 2. For the lifetime start/end intrinsics the pointer operand only
8581 // does anything useful when the input comes from a stack object,
8582 // which suggests it should always be uniform. For non-stack objects
8583 // the effect is to poison the object, which still allows us to
8584 // remove the call.
8585 IsUniform = true;
8586 break;
8587 default:
8588 break;
8589 }
8590 }
8591
8592 auto *Recipe = new VPReplicateRecipe(I, Plan->mapToVPValues(I->operands()),
8593 IsUniform, IsPredicated);
8594 setRecipe(I, Recipe);
8595 Plan->addVPValue(I, Recipe);
8596
8597 // Find if I uses a predicated instruction. If so, it will use its scalar
8598 // value. Avoid hoisting the insert-element which packs the scalar value into
8599 // a vector value, as that happens iff all users use the vector value.
8600 for (VPValue *Op : Recipe->operands()) {
8601 auto *PredR = dyn_cast_or_null<VPPredInstPHIRecipe>(Op->getDef());
8602 if (!PredR)
8603 continue;
8604 auto *RepR =
8605 cast_or_null<VPReplicateRecipe>(PredR->getOperand(0)->getDef());
8606 assert(RepR->isPredicated() &&(static_cast <bool> (RepR->isPredicated() &&
"expected Replicate recipe to be predicated") ? void (0) : __assert_fail
("RepR->isPredicated() && \"expected Replicate recipe to be predicated\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8607, __extension__
__PRETTY_FUNCTION__))
8607 "expected Replicate recipe to be predicated")(static_cast <bool> (RepR->isPredicated() &&
"expected Replicate recipe to be predicated") ? void (0) : __assert_fail
("RepR->isPredicated() && \"expected Replicate recipe to be predicated\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8607, __extension__
__PRETTY_FUNCTION__))
;
8608 RepR->setAlsoPack(false);
8609 }
8610
8611 // Finalize the recipe for Instr, first if it is not predicated.
8612 if (!IsPredicated) {
8613 LLVM_DEBUG(dbgs() << "LV: Scalarizing:" << *I << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Scalarizing:" <<
*I << "\n"; } } while (false)
;
8614 VPBB->appendRecipe(Recipe);
8615 return VPBB;
8616 }
8617 LLVM_DEBUG(dbgs() << "LV: Scalarizing and predicating:" << *I << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Scalarizing and predicating:"
<< *I << "\n"; } } while (false)
;
8618
8619 VPBlockBase *SingleSucc = VPBB->getSingleSuccessor();
8620 assert(SingleSucc && "VPBB must have a single successor when handling "(static_cast <bool> (SingleSucc && "VPBB must have a single successor when handling "
"predicated replication.") ? void (0) : __assert_fail ("SingleSucc && \"VPBB must have a single successor when handling \" \"predicated replication.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8621, __extension__
__PRETTY_FUNCTION__))
8621 "predicated replication.")(static_cast <bool> (SingleSucc && "VPBB must have a single successor when handling "
"predicated replication.") ? void (0) : __assert_fail ("SingleSucc && \"VPBB must have a single successor when handling \" \"predicated replication.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8621, __extension__
__PRETTY_FUNCTION__))
;
8622 VPBlockUtils::disconnectBlocks(VPBB, SingleSucc);
8623 // Record predicated instructions for above packing optimizations.
8624 VPBlockBase *Region = createReplicateRegion(I, Recipe, Plan);
8625 VPBlockUtils::insertBlockAfter(Region, VPBB);
8626 auto *RegSucc = new VPBasicBlock();
8627 VPBlockUtils::insertBlockAfter(RegSucc, Region);
8628 VPBlockUtils::connectBlocks(RegSucc, SingleSucc);
8629 return RegSucc;
8630}
8631
8632VPRegionBlock *VPRecipeBuilder::createReplicateRegion(Instruction *Instr,
8633 VPRecipeBase *PredRecipe,
8634 VPlanPtr &Plan) {
8635 // Instructions marked for predication are replicated and placed under an
8636 // if-then construct to prevent side-effects.
8637
8638 // Generate recipes to compute the block mask for this region.
8639 VPValue *BlockInMask = createBlockInMask(Instr->getParent(), Plan);
8640
8641 // Build the triangular if-then region.
8642 std::string RegionName = (Twine("pred.") + Instr->getOpcodeName()).str();
8643 assert(Instr->getParent() && "Predicated instruction not in any basic block")(static_cast <bool> (Instr->getParent() && "Predicated instruction not in any basic block"
) ? void (0) : __assert_fail ("Instr->getParent() && \"Predicated instruction not in any basic block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8643, __extension__
__PRETTY_FUNCTION__))
;
8644 auto *BOMRecipe = new VPBranchOnMaskRecipe(BlockInMask);
8645 auto *Entry = new VPBasicBlock(Twine(RegionName) + ".entry", BOMRecipe);
8646 auto *PHIRecipe = Instr->getType()->isVoidTy()
8647 ? nullptr
8648 : new VPPredInstPHIRecipe(Plan->getOrAddVPValue(Instr));
8649 if (PHIRecipe) {
8650 Plan->removeVPValueFor(Instr);
8651 Plan->addVPValue(Instr, PHIRecipe);
8652 }
8653 auto *Exit = new VPBasicBlock(Twine(RegionName) + ".continue", PHIRecipe);
8654 auto *Pred = new VPBasicBlock(Twine(RegionName) + ".if", PredRecipe);
8655 VPRegionBlock *Region = new VPRegionBlock(Entry, Exit, RegionName, true);
8656
8657 // Note: first set Entry as region entry and then connect successors starting
8658 // from it in order, to propagate the "parent" of each VPBasicBlock.
8659 VPBlockUtils::insertTwoBlocksAfter(Pred, Exit, BlockInMask, Entry);
8660 VPBlockUtils::connectBlocks(Pred, Exit);
8661
8662 return Region;
8663}
8664
8665VPRecipeOrVPValueTy
8666VPRecipeBuilder::tryToCreateWidenRecipe(Instruction *Instr,
8667 ArrayRef<VPValue *> Operands,
8668 VFRange &Range, VPlanPtr &Plan) {
8669 // First, check for specific widening recipes that deal with calls, memory
8670 // operations, inductions and Phi nodes.
8671 if (auto *CI = dyn_cast<CallInst>(Instr))
8672 return toVPRecipeResult(tryToWidenCall(CI, Operands, Range));
8673
8674 if (isa<LoadInst>(Instr) || isa<StoreInst>(Instr))
8675 return toVPRecipeResult(tryToWidenMemory(Instr, Operands, Range, Plan));
8676
8677 VPRecipeBase *Recipe;
8678 if (auto Phi = dyn_cast<PHINode>(Instr)) {
8679 if (Phi->getParent() != OrigLoop->getHeader())
8680 return tryToBlend(Phi, Operands, Plan);
8681 if ((Recipe = tryToOptimizeInductionPHI(Phi, Operands, Range)))
8682 return toVPRecipeResult(Recipe);
8683
8684 VPHeaderPHIRecipe *PhiRecipe = nullptr;
8685 if (Legal->isReductionVariable(Phi) || Legal->isFirstOrderRecurrence(Phi)) {
8686 VPValue *StartV = Operands[0];
8687 if (Legal->isReductionVariable(Phi)) {
8688 const RecurrenceDescriptor &RdxDesc =
8689 Legal->getReductionVars().find(Phi)->second;
8690 assert(RdxDesc.getRecurrenceStartValue() ==(static_cast <bool> (RdxDesc.getRecurrenceStartValue() ==
Phi->getIncomingValueForBlock(OrigLoop->getLoopPreheader
())) ? void (0) : __assert_fail ("RdxDesc.getRecurrenceStartValue() == Phi->getIncomingValueForBlock(OrigLoop->getLoopPreheader())"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8691, __extension__
__PRETTY_FUNCTION__))
8691 Phi->getIncomingValueForBlock(OrigLoop->getLoopPreheader()))(static_cast <bool> (RdxDesc.getRecurrenceStartValue() ==
Phi->getIncomingValueForBlock(OrigLoop->getLoopPreheader
())) ? void (0) : __assert_fail ("RdxDesc.getRecurrenceStartValue() == Phi->getIncomingValueForBlock(OrigLoop->getLoopPreheader())"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8691, __extension__
__PRETTY_FUNCTION__))
;
8692 PhiRecipe = new VPReductionPHIRecipe(Phi, RdxDesc, *StartV,
8693 CM.isInLoopReduction(Phi),
8694 CM.useOrderedReductions(RdxDesc));
8695 } else {
8696 PhiRecipe = new VPFirstOrderRecurrencePHIRecipe(Phi, *StartV);
8697 }
8698
8699 // Record the incoming value from the backedge, so we can add the incoming
8700 // value from the backedge after all recipes have been created.
8701 recordRecipeOf(cast<Instruction>(
8702 Phi->getIncomingValueForBlock(OrigLoop->getLoopLatch())));
8703 PhisToFix.push_back(PhiRecipe);
8704 } else {
8705 // TODO: record backedge value for remaining pointer induction phis.
8706 assert(Phi->getType()->isPointerTy() &&(static_cast <bool> (Phi->getType()->isPointerTy(
) && "only pointer phis should be handled here") ? void
(0) : __assert_fail ("Phi->getType()->isPointerTy() && \"only pointer phis should be handled here\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8707, __extension__
__PRETTY_FUNCTION__))
8707 "only pointer phis should be handled here")(static_cast <bool> (Phi->getType()->isPointerTy(
) && "only pointer phis should be handled here") ? void
(0) : __assert_fail ("Phi->getType()->isPointerTy() && \"only pointer phis should be handled here\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8707, __extension__
__PRETTY_FUNCTION__))
;
8708 assert(Legal->getInductionVars().count(Phi) &&(static_cast <bool> (Legal->getInductionVars().count
(Phi) && "Not an induction variable") ? void (0) : __assert_fail
("Legal->getInductionVars().count(Phi) && \"Not an induction variable\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8709, __extension__
__PRETTY_FUNCTION__))
8709 "Not an induction variable")(static_cast <bool> (Legal->getInductionVars().count
(Phi) && "Not an induction variable") ? void (0) : __assert_fail
("Legal->getInductionVars().count(Phi) && \"Not an induction variable\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8709, __extension__
__PRETTY_FUNCTION__))
;
8710 InductionDescriptor II = Legal->getInductionVars().lookup(Phi);
8711 VPValue *Start = Plan->getOrAddVPValue(II.getStartValue());
8712 PhiRecipe = new VPWidenPHIRecipe(Phi, Start);
8713 }
8714
8715 return toVPRecipeResult(PhiRecipe);
8716 }
8717
8718 if (isa<TruncInst>(Instr) &&
8719 (Recipe = tryToOptimizeInductionTruncate(cast<TruncInst>(Instr), Operands,
8720 Range, *Plan)))
8721 return toVPRecipeResult(Recipe);
8722
8723 if (!shouldWiden(Instr, Range))
8724 return nullptr;
8725
8726 if (auto GEP = dyn_cast<GetElementPtrInst>(Instr))
8727 return toVPRecipeResult(new VPWidenGEPRecipe(
8728 GEP, make_range(Operands.begin(), Operands.end()), OrigLoop));
8729
8730 if (auto *SI = dyn_cast<SelectInst>(Instr)) {
8731 bool InvariantCond =
8732 PSE.getSE()->isLoopInvariant(PSE.getSCEV(SI->getOperand(0)), OrigLoop);
8733 return toVPRecipeResult(new VPWidenSelectRecipe(
8734 *SI, make_range(Operands.begin(), Operands.end()), InvariantCond));
8735 }
8736
8737 return toVPRecipeResult(tryToWiden(Instr, Operands));
8738}
8739
8740void LoopVectorizationPlanner::buildVPlansWithVPRecipes(ElementCount MinVF,
8741 ElementCount MaxVF) {
8742 assert(OrigLoop->isInnermost() && "Inner loop expected.")(static_cast <bool> (OrigLoop->isInnermost() &&
"Inner loop expected.") ? void (0) : __assert_fail ("OrigLoop->isInnermost() && \"Inner loop expected.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8742, __extension__
__PRETTY_FUNCTION__))
;
8743
8744 // Collect instructions from the original loop that will become trivially dead
8745 // in the vectorized loop. We don't need to vectorize these instructions. For
8746 // example, original induction update instructions can become dead because we
8747 // separately emit induction "steps" when generating code for the new loop.
8748 // Similarly, we create a new latch condition when setting up the structure
8749 // of the new loop, so the old one can become dead.
8750 SmallPtrSet<Instruction *, 4> DeadInstructions;
8751 collectTriviallyDeadInstructions(DeadInstructions);
8752
8753 // Add assume instructions we need to drop to DeadInstructions, to prevent
8754 // them from being added to the VPlan.
8755 // TODO: We only need to drop assumes in blocks that get flattend. If the
8756 // control flow is preserved, we should keep them.
8757 auto &ConditionalAssumes = Legal->getConditionalAssumes();
8758 DeadInstructions.insert(ConditionalAssumes.begin(), ConditionalAssumes.end());
8759
8760 MapVector<Instruction *, Instruction *> &SinkAfter = Legal->getSinkAfter();
8761 // Dead instructions do not need sinking. Remove them from SinkAfter.
8762 for (Instruction *I : DeadInstructions)
8763 SinkAfter.erase(I);
8764
8765 // Cannot sink instructions after dead instructions (there won't be any
8766 // recipes for them). Instead, find the first non-dead previous instruction.
8767 for (auto &P : Legal->getSinkAfter()) {
8768 Instruction *SinkTarget = P.second;
8769 Instruction *FirstInst = &*SinkTarget->getParent()->begin();
8770 (void)FirstInst;
8771 while (DeadInstructions.contains(SinkTarget)) {
8772 assert((static_cast <bool> (SinkTarget != FirstInst &&
"Must find a live instruction (at least the one feeding the "
"first-order recurrence PHI) before reaching beginning of the block"
) ? void (0) : __assert_fail ("SinkTarget != FirstInst && \"Must find a live instruction (at least the one feeding the \" \"first-order recurrence PHI) before reaching beginning of the block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8775, __extension__
__PRETTY_FUNCTION__))
8773 SinkTarget != FirstInst &&(static_cast <bool> (SinkTarget != FirstInst &&
"Must find a live instruction (at least the one feeding the "
"first-order recurrence PHI) before reaching beginning of the block"
) ? void (0) : __assert_fail ("SinkTarget != FirstInst && \"Must find a live instruction (at least the one feeding the \" \"first-order recurrence PHI) before reaching beginning of the block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8775, __extension__
__PRETTY_FUNCTION__))
8774 "Must find a live instruction (at least the one feeding the "(static_cast <bool> (SinkTarget != FirstInst &&
"Must find a live instruction (at least the one feeding the "
"first-order recurrence PHI) before reaching beginning of the block"
) ? void (0) : __assert_fail ("SinkTarget != FirstInst && \"Must find a live instruction (at least the one feeding the \" \"first-order recurrence PHI) before reaching beginning of the block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8775, __extension__
__PRETTY_FUNCTION__))
8775 "first-order recurrence PHI) before reaching beginning of the block")(static_cast <bool> (SinkTarget != FirstInst &&
"Must find a live instruction (at least the one feeding the "
"first-order recurrence PHI) before reaching beginning of the block"
) ? void (0) : __assert_fail ("SinkTarget != FirstInst && \"Must find a live instruction (at least the one feeding the \" \"first-order recurrence PHI) before reaching beginning of the block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8775, __extension__
__PRETTY_FUNCTION__))
;
8776 SinkTarget = SinkTarget->getPrevNode();
8777 assert(SinkTarget != P.first &&(static_cast <bool> (SinkTarget != P.first && "sink source equals target, no sinking required"
) ? void (0) : __assert_fail ("SinkTarget != P.first && \"sink source equals target, no sinking required\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8778, __extension__
__PRETTY_FUNCTION__))
8778 "sink source equals target, no sinking required")(static_cast <bool> (SinkTarget != P.first && "sink source equals target, no sinking required"
) ? void (0) : __assert_fail ("SinkTarget != P.first && \"sink source equals target, no sinking required\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8778, __extension__
__PRETTY_FUNCTION__))
;
8779 }
8780 P.second = SinkTarget;
8781 }
8782
8783 auto MaxVFPlusOne = MaxVF.getWithIncrement(1);
8784 for (ElementCount VF = MinVF; ElementCount::isKnownLT(VF, MaxVFPlusOne);) {
8785 VFRange SubRange = {VF, MaxVFPlusOne};
8786 VPlans.push_back(
8787 buildVPlanWithVPRecipes(SubRange, DeadInstructions, SinkAfter));
8788 VF = SubRange.End;
8789 }
8790}
8791
8792// Add a VPCanonicalIVPHIRecipe starting at 0 to the header, a
8793// CanonicalIVIncrement{NUW} VPInstruction to increment it by VF * UF and a
8794// BranchOnCount VPInstruction to the latch.
8795static void addCanonicalIVRecipes(VPlan &Plan, Type *IdxTy, DebugLoc DL,
8796 bool HasNUW, bool IsVPlanNative) {
8797 Value *StartIdx = ConstantInt::get(IdxTy, 0);
8798 auto *StartV = Plan.getOrAddVPValue(StartIdx);
8799
8800 auto *CanonicalIVPHI = new VPCanonicalIVPHIRecipe(StartV, DL);
8801 VPRegionBlock *TopRegion = Plan.getVectorLoopRegion();
8802 VPBasicBlock *Header = TopRegion->getEntryBasicBlock();
8803 if (IsVPlanNative)
8804 Header = cast<VPBasicBlock>(Header->getSingleSuccessor());
8805 Header->insert(CanonicalIVPHI, Header->begin());
8806
8807 auto *CanonicalIVIncrement =
8808 new VPInstruction(HasNUW ? VPInstruction::CanonicalIVIncrementNUW
8809 : VPInstruction::CanonicalIVIncrement,
8810 {CanonicalIVPHI}, DL);
8811 CanonicalIVPHI->addOperand(CanonicalIVIncrement);
8812
8813 VPBasicBlock *EB = TopRegion->getExitBasicBlock();
8814 if (IsVPlanNative) {
8815 EB = cast<VPBasicBlock>(EB->getSinglePredecessor());
8816 EB->setCondBit(nullptr);
8817 }
8818 EB->appendRecipe(CanonicalIVIncrement);
8819
8820 auto *BranchOnCount =
8821 new VPInstruction(VPInstruction::BranchOnCount,
8822 {CanonicalIVIncrement, &Plan.getVectorTripCount()}, DL);
8823 EB->appendRecipe(BranchOnCount);
8824}
8825
8826VPlanPtr LoopVectorizationPlanner::buildVPlanWithVPRecipes(
8827 VFRange &Range, SmallPtrSetImpl<Instruction *> &DeadInstructions,
8828 const MapVector<Instruction *, Instruction *> &SinkAfter) {
8829
8830 SmallPtrSet<const InterleaveGroup<Instruction> *, 1> InterleaveGroups;
8831
8832 VPRecipeBuilder RecipeBuilder(OrigLoop, TLI, Legal, CM, PSE, Builder);
8833
8834 // ---------------------------------------------------------------------------
8835 // Pre-construction: record ingredients whose recipes we'll need to further
8836 // process after constructing the initial VPlan.
8837 // ---------------------------------------------------------------------------
8838
8839 // Mark instructions we'll need to sink later and their targets as
8840 // ingredients whose recipe we'll need to record.
8841 for (auto &Entry : SinkAfter) {
8842 RecipeBuilder.recordRecipeOf(Entry.first);
8843 RecipeBuilder.recordRecipeOf(Entry.second);
8844 }
8845 for (auto &Reduction : CM.getInLoopReductionChains()) {
8846 PHINode *Phi = Reduction.first;
8847 RecurKind Kind =
8848 Legal->getReductionVars().find(Phi)->second.getRecurrenceKind();
8849 const SmallVector<Instruction *, 4> &ReductionOperations = Reduction.second;
8850
8851 RecipeBuilder.recordRecipeOf(Phi);
8852 for (auto &R : ReductionOperations) {
8853 RecipeBuilder.recordRecipeOf(R);
8854 // For min/max reducitons, where we have a pair of icmp/select, we also
8855 // need to record the ICmp recipe, so it can be removed later.
8856 assert(!RecurrenceDescriptor::isSelectCmpRecurrenceKind(Kind) &&(static_cast <bool> (!RecurrenceDescriptor::isSelectCmpRecurrenceKind
(Kind) && "Only min/max recurrences allowed for inloop reductions"
) ? void (0) : __assert_fail ("!RecurrenceDescriptor::isSelectCmpRecurrenceKind(Kind) && \"Only min/max recurrences allowed for inloop reductions\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8857, __extension__
__PRETTY_FUNCTION__))
8857 "Only min/max recurrences allowed for inloop reductions")(static_cast <bool> (!RecurrenceDescriptor::isSelectCmpRecurrenceKind
(Kind) && "Only min/max recurrences allowed for inloop reductions"
) ? void (0) : __assert_fail ("!RecurrenceDescriptor::isSelectCmpRecurrenceKind(Kind) && \"Only min/max recurrences allowed for inloop reductions\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8857, __extension__
__PRETTY_FUNCTION__))
;
8858 if (RecurrenceDescriptor::isMinMaxRecurrenceKind(Kind))
8859 RecipeBuilder.recordRecipeOf(cast<Instruction>(R->getOperand(0)));
8860 }
8861 }
8862
8863 // For each interleave group which is relevant for this (possibly trimmed)
8864 // Range, add it to the set of groups to be later applied to the VPlan and add
8865 // placeholders for its members' Recipes which we'll be replacing with a
8866 // single VPInterleaveRecipe.
8867 for (InterleaveGroup<Instruction> *IG : IAI.getInterleaveGroups()) {
8868 auto applyIG = [IG, this](ElementCount VF) -> bool {
8869 return (VF.isVector() && // Query is illegal for VF == 1
8870 CM.getWideningDecision(IG->getInsertPos(), VF) ==
8871 LoopVectorizationCostModel::CM_Interleave);
8872 };
8873 if (!getDecisionAndClampRange(applyIG, Range))
8874 continue;
8875 InterleaveGroups.insert(IG);
8876 for (unsigned i = 0; i < IG->getFactor(); i++)
8877 if (Instruction *Member = IG->getMember(i))
8878 RecipeBuilder.recordRecipeOf(Member);
8879 };
8880
8881 // ---------------------------------------------------------------------------
8882 // Build initial VPlan: Scan the body of the loop in a topological order to
8883 // visit each basic block after having visited its predecessor basic blocks.
8884 // ---------------------------------------------------------------------------
8885
8886 // Create initial VPlan skeleton, with separate header and latch blocks.
8887 VPBasicBlock *HeaderVPBB = new VPBasicBlock();
8888 VPBasicBlock *LatchVPBB = new VPBasicBlock("vector.latch");
8889 VPBlockUtils::insertBlockAfter(LatchVPBB, HeaderVPBB);
8890 auto *TopRegion = new VPRegionBlock(HeaderVPBB, LatchVPBB, "vector loop");
8891 auto Plan = std::make_unique<VPlan>(TopRegion);
8892
8893 Instruction *DLInst =
8894 getDebugLocFromInstOrOperands(Legal->getPrimaryInduction());
8895 addCanonicalIVRecipes(*Plan, Legal->getWidestInductionType(),
8896 DLInst ? DLInst->getDebugLoc() : DebugLoc(),
8897 !CM.foldTailByMasking(), false);
8898
8899 // Scan the body of the loop in a topological order to visit each basic block
8900 // after having visited its predecessor basic blocks.
8901 LoopBlocksDFS DFS(OrigLoop);
8902 DFS.perform(LI);
8903
8904 VPBasicBlock *VPBB = HeaderVPBB;
8905 SmallVector<VPWidenIntOrFpInductionRecipe *> InductionsToMove;
8906 for (BasicBlock *BB : make_range(DFS.beginRPO(), DFS.endRPO())) {
8907 // Relevant instructions from basic block BB will be grouped into VPRecipe
8908 // ingredients and fill a new VPBasicBlock.
8909 unsigned VPBBsForBB = 0;
8910 VPBB->setName(BB->getName());
8911 Builder.setInsertPoint(VPBB);
8912
8913 // Introduce each ingredient into VPlan.
8914 // TODO: Model and preserve debug instrinsics in VPlan.
8915 for (Instruction &I : BB->instructionsWithoutDebug()) {
8916 Instruction *Instr = &I;
8917
8918 // First filter out irrelevant instructions, to ensure no recipes are
8919 // built for them.
8920 if (isa<BranchInst>(Instr) || DeadInstructions.count(Instr))
8921 continue;
8922
8923 SmallVector<VPValue *, 4> Operands;
8924 auto *Phi = dyn_cast<PHINode>(Instr);
8925 if (Phi && Phi->getParent() == OrigLoop->getHeader()) {
8926 Operands.push_back(Plan->getOrAddVPValue(
8927 Phi->getIncomingValueForBlock(OrigLoop->getLoopPreheader())));
8928 } else {
8929 auto OpRange = Plan->mapToVPValues(Instr->operands());
8930 Operands = {OpRange.begin(), OpRange.end()};
8931 }
8932 if (auto RecipeOrValue = RecipeBuilder.tryToCreateWidenRecipe(
8933 Instr, Operands, Range, Plan)) {
8934 // If Instr can be simplified to an existing VPValue, use it.
8935 if (RecipeOrValue.is<VPValue *>()) {
8936 auto *VPV = RecipeOrValue.get<VPValue *>();
8937 Plan->addVPValue(Instr, VPV);
8938 // If the re-used value is a recipe, register the recipe for the
8939 // instruction, in case the recipe for Instr needs to be recorded.
8940 if (auto *R = dyn_cast_or_null<VPRecipeBase>(VPV->getDef()))
8941 RecipeBuilder.setRecipe(Instr, R);
8942 continue;
8943 }
8944 // Otherwise, add the new recipe.
8945 VPRecipeBase *Recipe = RecipeOrValue.get<VPRecipeBase *>();
8946 for (auto *Def : Recipe->definedValues()) {
8947 auto *UV = Def->getUnderlyingValue();
8948 Plan->addVPValue(UV, Def);
8949 }
8950
8951 if (isa<VPWidenIntOrFpInductionRecipe>(Recipe) &&
8952 HeaderVPBB->getFirstNonPhi() != VPBB->end()) {
8953 // Keep track of VPWidenIntOrFpInductionRecipes not in the phi section
8954 // of the header block. That can happen for truncates of induction
8955 // variables. Those recipes are moved to the phi section of the header
8956 // block after applying SinkAfter, which relies on the original
8957 // position of the trunc.
8958 assert(isa<TruncInst>(Instr))(static_cast <bool> (isa<TruncInst>(Instr)) ? void
(0) : __assert_fail ("isa<TruncInst>(Instr)", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 8958, __extension__ __PRETTY_FUNCTION__))
;
8959 InductionsToMove.push_back(
8960 cast<VPWidenIntOrFpInductionRecipe>(Recipe));
8961 }
8962 RecipeBuilder.setRecipe(Instr, Recipe);
8963 VPBB->appendRecipe(Recipe);
8964 continue;
8965 }
8966
8967 // Otherwise, if all widening options failed, Instruction is to be
8968 // replicated. This may create a successor for VPBB.
8969 VPBasicBlock *NextVPBB =
8970 RecipeBuilder.handleReplication(Instr, Range, VPBB, Plan);
8971 if (NextVPBB != VPBB) {
8972 VPBB = NextVPBB;
8973 VPBB->setName(BB->hasName() ? BB->getName() + "." + Twine(VPBBsForBB++)
8974 : "");
8975 }
8976 }
8977
8978 VPBlockUtils::insertBlockAfter(new VPBasicBlock(), VPBB);
8979 VPBB = cast<VPBasicBlock>(VPBB->getSingleSuccessor());
8980 }
8981
8982 // Fold the last, empty block into its predecessor.
8983 VPBB = VPBlockUtils::tryToMergeBlockIntoPredecessor(VPBB);
8984 assert(VPBB && "expected to fold last (empty) block")(static_cast <bool> (VPBB && "expected to fold last (empty) block"
) ? void (0) : __assert_fail ("VPBB && \"expected to fold last (empty) block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8984, __extension__
__PRETTY_FUNCTION__))
;
8985 // After here, VPBB should not be used.
8986 VPBB = nullptr;
8987
8988 assert(isa<VPRegionBlock>(Plan->getEntry()) &&(static_cast <bool> (isa<VPRegionBlock>(Plan->
getEntry()) && !Plan->getEntry()->getEntryBasicBlock
()->empty() && "entry block must be set to a VPRegionBlock having a non-empty entry "
"VPBasicBlock") ? void (0) : __assert_fail ("isa<VPRegionBlock>(Plan->getEntry()) && !Plan->getEntry()->getEntryBasicBlock()->empty() && \"entry block must be set to a VPRegionBlock having a non-empty entry \" \"VPBasicBlock\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8991, __extension__
__PRETTY_FUNCTION__))
8989 !Plan->getEntry()->getEntryBasicBlock()->empty() &&(static_cast <bool> (isa<VPRegionBlock>(Plan->
getEntry()) && !Plan->getEntry()->getEntryBasicBlock
()->empty() && "entry block must be set to a VPRegionBlock having a non-empty entry "
"VPBasicBlock") ? void (0) : __assert_fail ("isa<VPRegionBlock>(Plan->getEntry()) && !Plan->getEntry()->getEntryBasicBlock()->empty() && \"entry block must be set to a VPRegionBlock having a non-empty entry \" \"VPBasicBlock\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8991, __extension__
__PRETTY_FUNCTION__))
8990 "entry block must be set to a VPRegionBlock having a non-empty entry "(static_cast <bool> (isa<VPRegionBlock>(Plan->
getEntry()) && !Plan->getEntry()->getEntryBasicBlock
()->empty() && "entry block must be set to a VPRegionBlock having a non-empty entry "
"VPBasicBlock") ? void (0) : __assert_fail ("isa<VPRegionBlock>(Plan->getEntry()) && !Plan->getEntry()->getEntryBasicBlock()->empty() && \"entry block must be set to a VPRegionBlock having a non-empty entry \" \"VPBasicBlock\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8991, __extension__
__PRETTY_FUNCTION__))
8991 "VPBasicBlock")(static_cast <bool> (isa<VPRegionBlock>(Plan->
getEntry()) && !Plan->getEntry()->getEntryBasicBlock
()->empty() && "entry block must be set to a VPRegionBlock having a non-empty entry "
"VPBasicBlock") ? void (0) : __assert_fail ("isa<VPRegionBlock>(Plan->getEntry()) && !Plan->getEntry()->getEntryBasicBlock()->empty() && \"entry block must be set to a VPRegionBlock having a non-empty entry \" \"VPBasicBlock\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 8991, __extension__
__PRETTY_FUNCTION__))
;
8992 RecipeBuilder.fixHeaderPhis();
8993
8994 // ---------------------------------------------------------------------------
8995 // Transform initial VPlan: Apply previously taken decisions, in order, to
8996 // bring the VPlan to its final state.
8997 // ---------------------------------------------------------------------------
8998
8999 // Apply Sink-After legal constraints.
9000 auto GetReplicateRegion = [](VPRecipeBase *R) -> VPRegionBlock * {
9001 auto *Region = dyn_cast_or_null<VPRegionBlock>(R->getParent()->getParent());
9002 if (Region && Region->isReplicator()) {
9003 assert(Region->getNumSuccessors() == 1 &&(static_cast <bool> (Region->getNumSuccessors() == 1
&& Region->getNumPredecessors() == 1 && "Expected SESE region!"
) ? void (0) : __assert_fail ("Region->getNumSuccessors() == 1 && Region->getNumPredecessors() == 1 && \"Expected SESE region!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9004, __extension__
__PRETTY_FUNCTION__))
9004 Region->getNumPredecessors() == 1 && "Expected SESE region!")(static_cast <bool> (Region->getNumSuccessors() == 1
&& Region->getNumPredecessors() == 1 && "Expected SESE region!"
) ? void (0) : __assert_fail ("Region->getNumSuccessors() == 1 && Region->getNumPredecessors() == 1 && \"Expected SESE region!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9004, __extension__
__PRETTY_FUNCTION__))
;
9005 assert(R->getParent()->size() == 1 &&(static_cast <bool> (R->getParent()->size() == 1 &&
"A recipe in an original replicator region must be the only "
"recipe in its block") ? void (0) : __assert_fail ("R->getParent()->size() == 1 && \"A recipe in an original replicator region must be the only \" \"recipe in its block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9007, __extension__
__PRETTY_FUNCTION__))
9006 "A recipe in an original replicator region must be the only "(static_cast <bool> (R->getParent()->size() == 1 &&
"A recipe in an original replicator region must be the only "
"recipe in its block") ? void (0) : __assert_fail ("R->getParent()->size() == 1 && \"A recipe in an original replicator region must be the only \" \"recipe in its block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9007, __extension__
__PRETTY_FUNCTION__))
9007 "recipe in its block")(static_cast <bool> (R->getParent()->size() == 1 &&
"A recipe in an original replicator region must be the only "
"recipe in its block") ? void (0) : __assert_fail ("R->getParent()->size() == 1 && \"A recipe in an original replicator region must be the only \" \"recipe in its block\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9007, __extension__
__PRETTY_FUNCTION__))
;
9008 return Region;
9009 }
9010 return nullptr;
9011 };
9012 for (auto &Entry : SinkAfter) {
9013 VPRecipeBase *Sink = RecipeBuilder.getRecipe(Entry.first);
9014 VPRecipeBase *Target = RecipeBuilder.getRecipe(Entry.second);
9015
9016 auto *TargetRegion = GetReplicateRegion(Target);
9017 auto *SinkRegion = GetReplicateRegion(Sink);
9018 if (!SinkRegion) {
9019 // If the sink source is not a replicate region, sink the recipe directly.
9020 if (TargetRegion) {
9021 // The target is in a replication region, make sure to move Sink to
9022 // the block after it, not into the replication region itself.
9023 VPBasicBlock *NextBlock =
9024 cast<VPBasicBlock>(TargetRegion->getSuccessors().front());
9025 Sink->moveBefore(*NextBlock, NextBlock->getFirstNonPhi());
9026 } else
9027 Sink->moveAfter(Target);
9028 continue;
9029 }
9030
9031 // The sink source is in a replicate region. Unhook the region from the CFG.
9032 auto *SinkPred = SinkRegion->getSinglePredecessor();
9033 auto *SinkSucc = SinkRegion->getSingleSuccessor();
9034 VPBlockUtils::disconnectBlocks(SinkPred, SinkRegion);
9035 VPBlockUtils::disconnectBlocks(SinkRegion, SinkSucc);
9036 VPBlockUtils::connectBlocks(SinkPred, SinkSucc);
9037
9038 if (TargetRegion) {
9039 // The target recipe is also in a replicate region, move the sink region
9040 // after the target region.
9041 auto *TargetSucc = TargetRegion->getSingleSuccessor();
9042 VPBlockUtils::disconnectBlocks(TargetRegion, TargetSucc);
9043 VPBlockUtils::connectBlocks(TargetRegion, SinkRegion);
9044 VPBlockUtils::connectBlocks(SinkRegion, TargetSucc);
9045 } else {
9046 // The sink source is in a replicate region, we need to move the whole
9047 // replicate region, which should only contain a single recipe in the
9048 // main block.
9049 auto *SplitBlock =
9050 Target->getParent()->splitAt(std::next(Target->getIterator()));
9051
9052 auto *SplitPred = SplitBlock->getSinglePredecessor();
9053
9054 VPBlockUtils::disconnectBlocks(SplitPred, SplitBlock);
9055 VPBlockUtils::connectBlocks(SplitPred, SinkRegion);
9056 VPBlockUtils::connectBlocks(SinkRegion, SplitBlock);
9057 }
9058 }
9059
9060 VPlanTransforms::removeRedundantCanonicalIVs(*Plan);
9061 VPlanTransforms::removeRedundantInductionCasts(*Plan);
9062
9063 // Now that sink-after is done, move induction recipes for optimized truncates
9064 // to the phi section of the header block.
9065 for (VPWidenIntOrFpInductionRecipe *Ind : InductionsToMove)
9066 Ind->moveBefore(*HeaderVPBB, HeaderVPBB->getFirstNonPhi());
9067
9068 // Adjust the recipes for any inloop reductions.
9069 adjustRecipesForReductions(cast<VPBasicBlock>(TopRegion->getExit()), Plan,
9070 RecipeBuilder, Range.Start);
9071
9072 // Introduce a recipe to combine the incoming and previous values of a
9073 // first-order recurrence.
9074 for (VPRecipeBase &R : Plan->getEntry()->getEntryBasicBlock()->phis()) {
9075 auto *RecurPhi = dyn_cast<VPFirstOrderRecurrencePHIRecipe>(&R);
9076 if (!RecurPhi)
9077 continue;
9078
9079 VPRecipeBase *PrevRecipe = RecurPhi->getBackedgeRecipe();
9080 VPBasicBlock *InsertBlock = PrevRecipe->getParent();
9081 auto *Region = GetReplicateRegion(PrevRecipe);
9082 if (Region)
9083 InsertBlock = cast<VPBasicBlock>(Region->getSingleSuccessor());
9084 if (Region || PrevRecipe->isPhi())
9085 Builder.setInsertPoint(InsertBlock, InsertBlock->getFirstNonPhi());
9086 else
9087 Builder.setInsertPoint(InsertBlock, std::next(PrevRecipe->getIterator()));
9088
9089 auto *RecurSplice = cast<VPInstruction>(
9090 Builder.createNaryOp(VPInstruction::FirstOrderRecurrenceSplice,
9091 {RecurPhi, RecurPhi->getBackedgeValue()}));
9092
9093 RecurPhi->replaceAllUsesWith(RecurSplice);
9094 // Set the first operand of RecurSplice to RecurPhi again, after replacing
9095 // all users.
9096 RecurSplice->setOperand(0, RecurPhi);
9097 }
9098
9099 // Interleave memory: for each Interleave Group we marked earlier as relevant
9100 // for this VPlan, replace the Recipes widening its memory instructions with a
9101 // single VPInterleaveRecipe at its insertion point.
9102 for (auto IG : InterleaveGroups) {
9103 auto *Recipe = cast<VPWidenMemoryInstructionRecipe>(
9104 RecipeBuilder.getRecipe(IG->getInsertPos()));
9105 SmallVector<VPValue *, 4> StoredValues;
9106 for (unsigned i = 0; i < IG->getFactor(); ++i)
9107 if (auto *SI = dyn_cast_or_null<StoreInst>(IG->getMember(i))) {
9108 auto *StoreR =
9109 cast<VPWidenMemoryInstructionRecipe>(RecipeBuilder.getRecipe(SI));
9110 StoredValues.push_back(StoreR->getStoredValue());
9111 }
9112
9113 auto *VPIG = new VPInterleaveRecipe(IG, Recipe->getAddr(), StoredValues,
9114 Recipe->getMask());
9115 VPIG->insertBefore(Recipe);
9116 unsigned J = 0;
9117 for (unsigned i = 0; i < IG->getFactor(); ++i)
9118 if (Instruction *Member = IG->getMember(i)) {
9119 if (!Member->getType()->isVoidTy()) {
9120 VPValue *OriginalV = Plan->getVPValue(Member);
9121 Plan->removeVPValueFor(Member);
9122 Plan->addVPValue(Member, VPIG->getVPValue(J));
9123 OriginalV->replaceAllUsesWith(VPIG->getVPValue(J));
9124 J++;
9125 }
9126 RecipeBuilder.getRecipe(Member)->eraseFromParent();
9127 }
9128 }
9129
9130 // From this point onwards, VPlan-to-VPlan transformations may change the plan
9131 // in ways that accessing values using original IR values is incorrect.
9132 Plan->disableValue2VPValue();
9133
9134 VPlanTransforms::optimizeInductions(*Plan, *PSE.getSE());
9135 VPlanTransforms::sinkScalarOperands(*Plan);
9136 VPlanTransforms::mergeReplicateRegions(*Plan);
9137 VPlanTransforms::removeDeadRecipes(*Plan, *OrigLoop);
9138
9139 std::string PlanName;
9140 raw_string_ostream RSO(PlanName);
9141 ElementCount VF = Range.Start;
9142 Plan->addVF(VF);
9143 RSO << "Initial VPlan for VF={" << VF;
9144 for (VF *= 2; ElementCount::isKnownLT(VF, Range.End); VF *= 2) {
9145 Plan->addVF(VF);
9146 RSO << "," << VF;
9147 }
9148 RSO << "},UF>=1";
9149 RSO.flush();
9150 Plan->setName(PlanName);
9151
9152 // Fold Exit block into its predecessor if possible.
9153 // TODO: Fold block earlier once all VPlan transforms properly maintain a
9154 // VPBasicBlock as exit.
9155 VPBlockUtils::tryToMergeBlockIntoPredecessor(TopRegion->getExit());
9156
9157 assert(VPlanVerifier::verifyPlanIsValid(*Plan) && "VPlan is invalid")(static_cast <bool> (VPlanVerifier::verifyPlanIsValid(*
Plan) && "VPlan is invalid") ? void (0) : __assert_fail
("VPlanVerifier::verifyPlanIsValid(*Plan) && \"VPlan is invalid\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9157, __extension__
__PRETTY_FUNCTION__))
;
9158 return Plan;
9159}
9160
9161VPlanPtr LoopVectorizationPlanner::buildVPlan(VFRange &Range) {
9162 // Outer loop handling: They may require CFG and instruction level
9163 // transformations before even evaluating whether vectorization is profitable.
9164 // Since we cannot modify the incoming IR, we need to build VPlan upfront in
9165 // the vectorization pipeline.
9166 assert(!OrigLoop->isInnermost())(static_cast <bool> (!OrigLoop->isInnermost()) ? void
(0) : __assert_fail ("!OrigLoop->isInnermost()", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 9166, __extension__ __PRETTY_FUNCTION__))
;
9167 assert(EnableVPlanNativePath && "VPlan-native path is not enabled.")(static_cast <bool> (EnableVPlanNativePath && "VPlan-native path is not enabled."
) ? void (0) : __assert_fail ("EnableVPlanNativePath && \"VPlan-native path is not enabled.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9167, __extension__
__PRETTY_FUNCTION__))
;
9168
9169 // Create new empty VPlan
9170 auto Plan = std::make_unique<VPlan>();
9171
9172 // Build hierarchical CFG
9173 VPlanHCFGBuilder HCFGBuilder(OrigLoop, LI, *Plan);
9174 HCFGBuilder.buildHierarchicalCFG();
9175
9176 for (ElementCount VF = Range.Start; ElementCount::isKnownLT(VF, Range.End);
9177 VF *= 2)
9178 Plan->addVF(VF);
9179
9180 if (EnableVPlanPredication) {
9181 VPlanPredicator VPP(*Plan);
9182 VPP.predicate();
9183
9184 // Avoid running transformation to recipes until masked code generation in
9185 // VPlan-native path is in place.
9186 return Plan;
9187 }
9188
9189 SmallPtrSet<Instruction *, 1> DeadInstructions;
9190 VPlanTransforms::VPInstructionsToVPRecipes(
9191 OrigLoop, Plan,
9192 [this](PHINode *P) { return Legal->getIntOrFpInductionDescriptor(P); },
9193 DeadInstructions, *PSE.getSE());
9194
9195 addCanonicalIVRecipes(*Plan, Legal->getWidestInductionType(), DebugLoc(),
9196 true, true);
9197 return Plan;
9198}
9199
9200// Adjust the recipes for reductions. For in-loop reductions the chain of
9201// instructions leading from the loop exit instr to the phi need to be converted
9202// to reductions, with one operand being vector and the other being the scalar
9203// reduction chain. For other reductions, a select is introduced between the phi
9204// and live-out recipes when folding the tail.
9205void LoopVectorizationPlanner::adjustRecipesForReductions(
9206 VPBasicBlock *LatchVPBB, VPlanPtr &Plan, VPRecipeBuilder &RecipeBuilder,
9207 ElementCount MinVF) {
9208 for (auto &Reduction : CM.getInLoopReductionChains()) {
9209 PHINode *Phi = Reduction.first;
9210 const RecurrenceDescriptor &RdxDesc =
9211 Legal->getReductionVars().find(Phi)->second;
9212 const SmallVector<Instruction *, 4> &ReductionOperations = Reduction.second;
9213
9214 if (MinVF.isScalar() && !CM.useOrderedReductions(RdxDesc))
9215 continue;
9216
9217 // ReductionOperations are orders top-down from the phi's use to the
9218 // LoopExitValue. We keep a track of the previous item (the Chain) to tell
9219 // which of the two operands will remain scalar and which will be reduced.
9220 // For minmax the chain will be the select instructions.
9221 Instruction *Chain = Phi;
9222 for (Instruction *R : ReductionOperations) {
9223 VPRecipeBase *WidenRecipe = RecipeBuilder.getRecipe(R);
9224 RecurKind Kind = RdxDesc.getRecurrenceKind();
9225
9226 VPValue *ChainOp = Plan->getVPValue(Chain);
9227 unsigned FirstOpId;
9228 assert(!RecurrenceDescriptor::isSelectCmpRecurrenceKind(Kind) &&(static_cast <bool> (!RecurrenceDescriptor::isSelectCmpRecurrenceKind
(Kind) && "Only min/max recurrences allowed for inloop reductions"
) ? void (0) : __assert_fail ("!RecurrenceDescriptor::isSelectCmpRecurrenceKind(Kind) && \"Only min/max recurrences allowed for inloop reductions\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9229, __extension__
__PRETTY_FUNCTION__))
9229 "Only min/max recurrences allowed for inloop reductions")(static_cast <bool> (!RecurrenceDescriptor::isSelectCmpRecurrenceKind
(Kind) && "Only min/max recurrences allowed for inloop reductions"
) ? void (0) : __assert_fail ("!RecurrenceDescriptor::isSelectCmpRecurrenceKind(Kind) && \"Only min/max recurrences allowed for inloop reductions\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9229, __extension__
__PRETTY_FUNCTION__))
;
9230 // Recognize a call to the llvm.fmuladd intrinsic.
9231 bool IsFMulAdd = (Kind == RecurKind::FMulAdd);
9232 assert((!IsFMulAdd || RecurrenceDescriptor::isFMulAddIntrinsic(R)) &&(static_cast <bool> ((!IsFMulAdd || RecurrenceDescriptor
::isFMulAddIntrinsic(R)) && "Expected instruction to be a call to the llvm.fmuladd intrinsic"
) ? void (0) : __assert_fail ("(!IsFMulAdd || RecurrenceDescriptor::isFMulAddIntrinsic(R)) && \"Expected instruction to be a call to the llvm.fmuladd intrinsic\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9233, __extension__
__PRETTY_FUNCTION__))
9233 "Expected instruction to be a call to the llvm.fmuladd intrinsic")(static_cast <bool> ((!IsFMulAdd || RecurrenceDescriptor
::isFMulAddIntrinsic(R)) && "Expected instruction to be a call to the llvm.fmuladd intrinsic"
) ? void (0) : __assert_fail ("(!IsFMulAdd || RecurrenceDescriptor::isFMulAddIntrinsic(R)) && \"Expected instruction to be a call to the llvm.fmuladd intrinsic\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9233, __extension__
__PRETTY_FUNCTION__))
;
9234 if (RecurrenceDescriptor::isMinMaxRecurrenceKind(Kind)) {
9235 assert(isa<VPWidenSelectRecipe>(WidenRecipe) &&(static_cast <bool> (isa<VPWidenSelectRecipe>(WidenRecipe
) && "Expected to replace a VPWidenSelectSC") ? void (
0) : __assert_fail ("isa<VPWidenSelectRecipe>(WidenRecipe) && \"Expected to replace a VPWidenSelectSC\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9236, __extension__
__PRETTY_FUNCTION__))
9236 "Expected to replace a VPWidenSelectSC")(static_cast <bool> (isa<VPWidenSelectRecipe>(WidenRecipe
) && "Expected to replace a VPWidenSelectSC") ? void (
0) : __assert_fail ("isa<VPWidenSelectRecipe>(WidenRecipe) && \"Expected to replace a VPWidenSelectSC\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9236, __extension__
__PRETTY_FUNCTION__))
;
9237 FirstOpId = 1;
9238 } else {
9239 assert((MinVF.isScalar() || isa<VPWidenRecipe>(WidenRecipe) ||(static_cast <bool> ((MinVF.isScalar() || isa<VPWidenRecipe
>(WidenRecipe) || (IsFMulAdd && isa<VPWidenCallRecipe
>(WidenRecipe))) && "Expected to replace a VPWidenSC"
) ? void (0) : __assert_fail ("(MinVF.isScalar() || isa<VPWidenRecipe>(WidenRecipe) || (IsFMulAdd && isa<VPWidenCallRecipe>(WidenRecipe))) && \"Expected to replace a VPWidenSC\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9241, __extension__
__PRETTY_FUNCTION__))
9240 (IsFMulAdd && isa<VPWidenCallRecipe>(WidenRecipe))) &&(static_cast <bool> ((MinVF.isScalar() || isa<VPWidenRecipe
>(WidenRecipe) || (IsFMulAdd && isa<VPWidenCallRecipe
>(WidenRecipe))) && "Expected to replace a VPWidenSC"
) ? void (0) : __assert_fail ("(MinVF.isScalar() || isa<VPWidenRecipe>(WidenRecipe) || (IsFMulAdd && isa<VPWidenCallRecipe>(WidenRecipe))) && \"Expected to replace a VPWidenSC\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9241, __extension__
__PRETTY_FUNCTION__))
9241 "Expected to replace a VPWidenSC")(static_cast <bool> ((MinVF.isScalar() || isa<VPWidenRecipe
>(WidenRecipe) || (IsFMulAdd && isa<VPWidenCallRecipe
>(WidenRecipe))) && "Expected to replace a VPWidenSC"
) ? void (0) : __assert_fail ("(MinVF.isScalar() || isa<VPWidenRecipe>(WidenRecipe) || (IsFMulAdd && isa<VPWidenCallRecipe>(WidenRecipe))) && \"Expected to replace a VPWidenSC\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9241, __extension__
__PRETTY_FUNCTION__))
;
9242 FirstOpId = 0;
9243 }
9244 unsigned VecOpId =
9245 R->getOperand(FirstOpId) == Chain ? FirstOpId + 1 : FirstOpId;
9246 VPValue *VecOp = Plan->getVPValue(R->getOperand(VecOpId));
9247
9248 auto *CondOp = CM.blockNeedsPredicationForAnyReason(R->getParent())
9249 ? RecipeBuilder.createBlockInMask(R->getParent(), Plan)
9250 : nullptr;
9251
9252 if (IsFMulAdd) {
9253 // If the instruction is a call to the llvm.fmuladd intrinsic then we
9254 // need to create an fmul recipe to use as the vector operand for the
9255 // fadd reduction.
9256 VPInstruction *FMulRecipe = new VPInstruction(
9257 Instruction::FMul, {VecOp, Plan->getVPValue(R->getOperand(1))});
9258 FMulRecipe->setFastMathFlags(R->getFastMathFlags());
9259 WidenRecipe->getParent()->insert(FMulRecipe,
9260 WidenRecipe->getIterator());
9261 VecOp = FMulRecipe;
9262 }
9263 VPReductionRecipe *RedRecipe =
9264 new VPReductionRecipe(&RdxDesc, R, ChainOp, VecOp, CondOp, TTI);
9265 WidenRecipe->getVPSingleValue()->replaceAllUsesWith(RedRecipe);
9266 Plan->removeVPValueFor(R);
9267 Plan->addVPValue(R, RedRecipe);
9268 WidenRecipe->getParent()->insert(RedRecipe, WidenRecipe->getIterator());
9269 WidenRecipe->getVPSingleValue()->replaceAllUsesWith(RedRecipe);
9270 WidenRecipe->eraseFromParent();
9271
9272 if (RecurrenceDescriptor::isMinMaxRecurrenceKind(Kind)) {
9273 VPRecipeBase *CompareRecipe =
9274 RecipeBuilder.getRecipe(cast<Instruction>(R->getOperand(0)));
9275 assert(isa<VPWidenRecipe>(CompareRecipe) &&(static_cast <bool> (isa<VPWidenRecipe>(CompareRecipe
) && "Expected to replace a VPWidenSC") ? void (0) : __assert_fail
("isa<VPWidenRecipe>(CompareRecipe) && \"Expected to replace a VPWidenSC\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9276, __extension__
__PRETTY_FUNCTION__))
9276 "Expected to replace a VPWidenSC")(static_cast <bool> (isa<VPWidenRecipe>(CompareRecipe
) && "Expected to replace a VPWidenSC") ? void (0) : __assert_fail
("isa<VPWidenRecipe>(CompareRecipe) && \"Expected to replace a VPWidenSC\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9276, __extension__
__PRETTY_FUNCTION__))
;
9277 assert(cast<VPWidenRecipe>(CompareRecipe)->getNumUsers() == 0 &&(static_cast <bool> (cast<VPWidenRecipe>(CompareRecipe
)->getNumUsers() == 0 && "Expected no remaining users"
) ? void (0) : __assert_fail ("cast<VPWidenRecipe>(CompareRecipe)->getNumUsers() == 0 && \"Expected no remaining users\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9278, __extension__
__PRETTY_FUNCTION__))
9278 "Expected no remaining users")(static_cast <bool> (cast<VPWidenRecipe>(CompareRecipe
)->getNumUsers() == 0 && "Expected no remaining users"
) ? void (0) : __assert_fail ("cast<VPWidenRecipe>(CompareRecipe)->getNumUsers() == 0 && \"Expected no remaining users\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9278, __extension__
__PRETTY_FUNCTION__))
;
9279 CompareRecipe->eraseFromParent();
9280 }
9281 Chain = R;
9282 }
9283 }
9284
9285 // If tail is folded by masking, introduce selects between the phi
9286 // and the live-out instruction of each reduction, at the beginning of the
9287 // dedicated latch block.
9288 if (CM.foldTailByMasking()) {
9289 Builder.setInsertPoint(LatchVPBB, LatchVPBB->begin());
9290 for (VPRecipeBase &R : Plan->getEntry()->getEntryBasicBlock()->phis()) {
9291 VPReductionPHIRecipe *PhiR = dyn_cast<VPReductionPHIRecipe>(&R);
9292 if (!PhiR || PhiR->isInLoop())
9293 continue;
9294 VPValue *Cond =
9295 RecipeBuilder.createBlockInMask(OrigLoop->getHeader(), Plan);
9296 VPValue *Red = PhiR->getBackedgeValue();
9297 assert(cast<VPRecipeBase>(Red->getDef())->getParent() != LatchVPBB &&(static_cast <bool> (cast<VPRecipeBase>(Red->getDef
())->getParent() != LatchVPBB && "reduction recipe must be defined before latch"
) ? void (0) : __assert_fail ("cast<VPRecipeBase>(Red->getDef())->getParent() != LatchVPBB && \"reduction recipe must be defined before latch\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9298, __extension__
__PRETTY_FUNCTION__))
9298 "reduction recipe must be defined before latch")(static_cast <bool> (cast<VPRecipeBase>(Red->getDef
())->getParent() != LatchVPBB && "reduction recipe must be defined before latch"
) ? void (0) : __assert_fail ("cast<VPRecipeBase>(Red->getDef())->getParent() != LatchVPBB && \"reduction recipe must be defined before latch\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9298, __extension__
__PRETTY_FUNCTION__))
;
9299 Builder.createNaryOp(Instruction::Select, {Cond, Red, PhiR});
9300 }
9301 }
9302}
9303
9304#if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP)
9305void VPInterleaveRecipe::print(raw_ostream &O, const Twine &Indent,
9306 VPSlotTracker &SlotTracker) const {
9307 O << Indent << "INTERLEAVE-GROUP with factor " << IG->getFactor() << " at ";
9308 IG->getInsertPos()->printAsOperand(O, false);
9309 O << ", ";
9310 getAddr()->printAsOperand(O, SlotTracker);
9311 VPValue *Mask = getMask();
9312 if (Mask) {
9313 O << ", ";
9314 Mask->printAsOperand(O, SlotTracker);
9315 }
9316
9317 unsigned OpIdx = 0;
9318 for (unsigned i = 0; i < IG->getFactor(); ++i) {
9319 if (!IG->getMember(i))
9320 continue;
9321 if (getNumStoreOperands() > 0) {
9322 O << "\n" << Indent << " store ";
9323 getOperand(1 + OpIdx)->printAsOperand(O, SlotTracker);
9324 O << " to index " << i;
9325 } else {
9326 O << "\n" << Indent << " ";
9327 getVPValue(OpIdx)->printAsOperand(O, SlotTracker);
9328 O << " = load from index " << i;
9329 }
9330 ++OpIdx;
9331 }
9332}
9333#endif
9334
9335void VPWidenCallRecipe::execute(VPTransformState &State) {
9336 State.ILV->widenCallInstruction(*cast<CallInst>(getUnderlyingInstr()), this,
9337 *this, State);
9338}
9339
9340void VPWidenSelectRecipe::execute(VPTransformState &State) {
9341 auto &I = *cast<SelectInst>(getUnderlyingInstr());
9342 State.ILV->setDebugLocFromInst(&I);
9343
9344 // The condition can be loop invariant but still defined inside the
9345 // loop. This means that we can't just use the original 'cond' value.
9346 // We have to take the 'vectorized' value and pick the first lane.
9347 // Instcombine will make this a no-op.
9348 auto *InvarCond =
9349 InvariantCond ? State.get(getOperand(0), VPIteration(0, 0)) : nullptr;
9350
9351 for (unsigned Part = 0; Part < State.UF; ++Part) {
9352 Value *Cond = InvarCond ? InvarCond : State.get(getOperand(0), Part);
9353 Value *Op0 = State.get(getOperand(1), Part);
9354 Value *Op1 = State.get(getOperand(2), Part);
9355 Value *Sel = State.Builder.CreateSelect(Cond, Op0, Op1);
9356 State.set(this, Sel, Part);
9357 State.ILV->addMetadata(Sel, &I);
9358 }
9359}
9360
9361void VPWidenRecipe::execute(VPTransformState &State) {
9362 auto &I = *cast<Instruction>(getUnderlyingValue());
9363 auto &Builder = State.Builder;
9364 switch (I.getOpcode()) {
9365 case Instruction::Call:
9366 case Instruction::Br:
9367 case Instruction::PHI:
9368 case Instruction::GetElementPtr:
9369 case Instruction::Select:
9370 llvm_unreachable("This instruction is handled by a different recipe.")::llvm::llvm_unreachable_internal("This instruction is handled by a different recipe."
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9370)
;
9371 case Instruction::UDiv:
9372 case Instruction::SDiv:
9373 case Instruction::SRem:
9374 case Instruction::URem:
9375 case Instruction::Add:
9376 case Instruction::FAdd:
9377 case Instruction::Sub:
9378 case Instruction::FSub:
9379 case Instruction::FNeg:
9380 case Instruction::Mul:
9381 case Instruction::FMul:
9382 case Instruction::FDiv:
9383 case Instruction::FRem:
9384 case Instruction::Shl:
9385 case Instruction::LShr:
9386 case Instruction::AShr:
9387 case Instruction::And:
9388 case Instruction::Or:
9389 case Instruction::Xor: {
9390 // Just widen unops and binops.
9391 State.ILV->setDebugLocFromInst(&I);
9392
9393 for (unsigned Part = 0; Part < State.UF; ++Part) {
9394 SmallVector<Value *, 2> Ops;
9395 for (VPValue *VPOp : operands())
9396 Ops.push_back(State.get(VPOp, Part));
9397
9398 Value *V = Builder.CreateNAryOp(I.getOpcode(), Ops);
9399
9400 if (auto *VecOp = dyn_cast<Instruction>(V)) {
9401 VecOp->copyIRFlags(&I);
9402
9403 // If the instruction is vectorized and was in a basic block that needed
9404 // predication, we can't propagate poison-generating flags (nuw/nsw,
9405 // exact, etc.). The control flow has been linearized and the
9406 // instruction is no longer guarded by the predicate, which could make
9407 // the flag properties to no longer hold.
9408 if (State.MayGeneratePoisonRecipes.contains(this))
9409 VecOp->dropPoisonGeneratingFlags();
9410 }
9411
9412 // Use this vector value for all users of the original instruction.
9413 State.set(this, V, Part);
9414 State.ILV->addMetadata(V, &I);
9415 }
9416
9417 break;
9418 }
9419 case Instruction::ICmp:
9420 case Instruction::FCmp: {
9421 // Widen compares. Generate vector compares.
9422 bool FCmp = (I.getOpcode() == Instruction::FCmp);
9423 auto *Cmp = cast<CmpInst>(&I);
9424 State.ILV->setDebugLocFromInst(Cmp);
9425 for (unsigned Part = 0; Part < State.UF; ++Part) {
9426 Value *A = State.get(getOperand(0), Part);
9427 Value *B = State.get(getOperand(1), Part);
9428 Value *C = nullptr;
9429 if (FCmp) {
9430 // Propagate fast math flags.
9431 IRBuilder<>::FastMathFlagGuard FMFG(Builder);
9432 Builder.setFastMathFlags(Cmp->getFastMathFlags());
9433 C = Builder.CreateFCmp(Cmp->getPredicate(), A, B);
9434 } else {
9435 C = Builder.CreateICmp(Cmp->getPredicate(), A, B);
9436 }
9437 State.set(this, C, Part);
9438 State.ILV->addMetadata(C, &I);
9439 }
9440
9441 break;
9442 }
9443
9444 case Instruction::ZExt:
9445 case Instruction::SExt:
9446 case Instruction::FPToUI:
9447 case Instruction::FPToSI:
9448 case Instruction::FPExt:
9449 case Instruction::PtrToInt:
9450 case Instruction::IntToPtr:
9451 case Instruction::SIToFP:
9452 case Instruction::UIToFP:
9453 case Instruction::Trunc:
9454 case Instruction::FPTrunc:
9455 case Instruction::BitCast: {
9456 auto *CI = cast<CastInst>(&I);
9457 State.ILV->setDebugLocFromInst(CI);
9458
9459 /// Vectorize casts.
9460 Type *DestTy = (State.VF.isScalar())
9461 ? CI->getType()
9462 : VectorType::get(CI->getType(), State.VF);
9463
9464 for (unsigned Part = 0; Part < State.UF; ++Part) {
9465 Value *A = State.get(getOperand(0), Part);
9466 Value *Cast = Builder.CreateCast(CI->getOpcode(), A, DestTy);
9467 State.set(this, Cast, Part);
9468 State.ILV->addMetadata(Cast, &I);
9469 }
9470 break;
9471 }
9472 default:
9473 // This instruction is not vectorized by simple widening.
9474 LLVM_DEBUG(dbgs() << "LV: Found an unhandled instruction: " << I)do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found an unhandled instruction: "
<< I; } } while (false)
;
9475 llvm_unreachable("Unhandled instruction!")::llvm::llvm_unreachable_internal("Unhandled instruction!", "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp"
, 9475)
;
9476 } // end of switch.
9477}
9478
9479void VPWidenGEPRecipe::execute(VPTransformState &State) {
9480 auto *GEP = cast<GetElementPtrInst>(getUnderlyingInstr());
9481 // Construct a vector GEP by widening the operands of the scalar GEP as
9482 // necessary. We mark the vector GEP 'inbounds' if appropriate. A GEP
9483 // results in a vector of pointers when at least one operand of the GEP
9484 // is vector-typed. Thus, to keep the representation compact, we only use
9485 // vector-typed operands for loop-varying values.
9486
9487 if (State.VF.isVector() && IsPtrLoopInvariant && IsIndexLoopInvariant.all()) {
9488 // If we are vectorizing, but the GEP has only loop-invariant operands,
9489 // the GEP we build (by only using vector-typed operands for
9490 // loop-varying values) would be a scalar pointer. Thus, to ensure we
9491 // produce a vector of pointers, we need to either arbitrarily pick an
9492 // operand to broadcast, or broadcast a clone of the original GEP.
9493 // Here, we broadcast a clone of the original.
9494 //
9495 // TODO: If at some point we decide to scalarize instructions having
9496 // loop-invariant operands, this special case will no longer be
9497 // required. We would add the scalarization decision to
9498 // collectLoopScalars() and teach getVectorValue() to broadcast
9499 // the lane-zero scalar value.
9500 auto *Clone = State.Builder.Insert(GEP->clone());
9501 for (unsigned Part = 0; Part < State.UF; ++Part) {
9502 Value *EntryPart = State.Builder.CreateVectorSplat(State.VF, Clone);
9503 State.set(this, EntryPart, Part);
9504 State.ILV->addMetadata(EntryPart, GEP);
9505 }
9506 } else {
9507 // If the GEP has at least one loop-varying operand, we are sure to
9508 // produce a vector of pointers. But if we are only unrolling, we want
9509 // to produce a scalar GEP for each unroll part. Thus, the GEP we
9510 // produce with the code below will be scalar (if VF == 1) or vector
9511 // (otherwise). Note that for the unroll-only case, we still maintain
9512 // values in the vector mapping with initVector, as we do for other
9513 // instructions.
9514 for (unsigned Part = 0; Part < State.UF; ++Part) {
9515 // The pointer operand of the new GEP. If it's loop-invariant, we
9516 // won't broadcast it.
9517 auto *Ptr = IsPtrLoopInvariant
9518 ? State.get(getOperand(0), VPIteration(0, 0))
9519 : State.get(getOperand(0), Part);
9520
9521 // Collect all the indices for the new GEP. If any index is
9522 // loop-invariant, we won't broadcast it.
9523 SmallVector<Value *, 4> Indices;
9524 for (unsigned I = 1, E = getNumOperands(); I < E; I++) {
9525 VPValue *Operand = getOperand(I);
9526 if (IsIndexLoopInvariant[I - 1])
9527 Indices.push_back(State.get(Operand, VPIteration(0, 0)));
9528 else
9529 Indices.push_back(State.get(Operand, Part));
9530 }
9531
9532 // If the GEP instruction is vectorized and was in a basic block that
9533 // needed predication, we can't propagate the poison-generating 'inbounds'
9534 // flag. The control flow has been linearized and the GEP is no longer
9535 // guarded by the predicate, which could make the 'inbounds' properties to
9536 // no longer hold.
9537 bool IsInBounds =
9538 GEP->isInBounds() && State.MayGeneratePoisonRecipes.count(this) == 0;
9539
9540 // Create the new GEP. Note that this GEP may be a scalar if VF == 1,
9541 // but it should be a vector, otherwise.
9542 auto *NewGEP = IsInBounds
9543 ? State.Builder.CreateInBoundsGEP(
9544 GEP->getSourceElementType(), Ptr, Indices)
9545 : State.Builder.CreateGEP(GEP->getSourceElementType(),
9546 Ptr, Indices);
9547 assert((State.VF.isScalar() || NewGEP->getType()->isVectorTy()) &&(static_cast <bool> ((State.VF.isScalar() || NewGEP->
getType()->isVectorTy()) && "NewGEP is not a pointer vector"
) ? void (0) : __assert_fail ("(State.VF.isScalar() || NewGEP->getType()->isVectorTy()) && \"NewGEP is not a pointer vector\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9548, __extension__
__PRETTY_FUNCTION__))
9548 "NewGEP is not a pointer vector")(static_cast <bool> ((State.VF.isScalar() || NewGEP->
getType()->isVectorTy()) && "NewGEP is not a pointer vector"
) ? void (0) : __assert_fail ("(State.VF.isScalar() || NewGEP->getType()->isVectorTy()) && \"NewGEP is not a pointer vector\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9548, __extension__
__PRETTY_FUNCTION__))
;
9549 State.set(this, NewGEP, Part);
9550 State.ILV->addMetadata(NewGEP, GEP);
9551 }
9552 }
9553}
9554
9555void VPWidenIntOrFpInductionRecipe::execute(VPTransformState &State) {
9556 assert(!State.Instance && "Int or FP induction being replicated.")(static_cast <bool> (!State.Instance && "Int or FP induction being replicated."
) ? void (0) : __assert_fail ("!State.Instance && \"Int or FP induction being replicated.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9556, __extension__
__PRETTY_FUNCTION__))
;
9557
9558 Value *Start = getStartValue()->getLiveInIRValue();
9559 const InductionDescriptor &ID = getInductionDescriptor();
9560 TruncInst *Trunc = getTruncInst();
9561 IRBuilderBase &Builder = State.Builder;
9562 assert(IV->getType() == ID.getStartValue()->getType() && "Types must match")(static_cast <bool> (IV->getType() == ID.getStartValue
()->getType() && "Types must match") ? void (0) : __assert_fail
("IV->getType() == ID.getStartValue()->getType() && \"Types must match\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9562, __extension__
__PRETTY_FUNCTION__))
;
9563 assert(State.VF.isVector() && "must have vector VF")(static_cast <bool> (State.VF.isVector() && "must have vector VF"
) ? void (0) : __assert_fail ("State.VF.isVector() && \"must have vector VF\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9563, __extension__
__PRETTY_FUNCTION__))
;
9564
9565 // The value from the original loop to which we are mapping the new induction
9566 // variable.
9567 Instruction *EntryVal = Trunc ? cast<Instruction>(Trunc) : IV;
9568
9569 auto &DL = EntryVal->getModule()->getDataLayout();
9570
9571 // Generate code for the induction step. Note that induction steps are
9572 // required to be loop-invariant
9573 auto CreateStepValue = [&](const SCEV *Step) -> Value * {
9574 if (SE.isSCEVable(IV->getType())) {
9575 SCEVExpander Exp(SE, DL, "induction");
9576 return Exp.expandCodeFor(Step, Step->getType(),
9577 State.CFG.VectorPreHeader->getTerminator());
9578 }
9579 return cast<SCEVUnknown>(Step)->getValue();
9580 };
9581
9582 // Fast-math-flags propagate from the original induction instruction.
9583 IRBuilder<>::FastMathFlagGuard FMFG(Builder);
9584 if (ID.getInductionBinOp() && isa<FPMathOperator>(ID.getInductionBinOp()))
9585 Builder.setFastMathFlags(ID.getInductionBinOp()->getFastMathFlags());
9586
9587 // Now do the actual transformations, and start with creating the step value.
9588 Value *Step = CreateStepValue(ID.getStep());
9589
9590 assert((isa<PHINode>(EntryVal) || isa<TruncInst>(EntryVal)) &&(static_cast <bool> ((isa<PHINode>(EntryVal) || isa
<TruncInst>(EntryVal)) && "Expected either an induction phi-node or a truncate of it!"
) ? void (0) : __assert_fail ("(isa<PHINode>(EntryVal) || isa<TruncInst>(EntryVal)) && \"Expected either an induction phi-node or a truncate of it!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9591, __extension__
__PRETTY_FUNCTION__))
9591 "Expected either an induction phi-node or a truncate of it!")(static_cast <bool> ((isa<PHINode>(EntryVal) || isa
<TruncInst>(EntryVal)) && "Expected either an induction phi-node or a truncate of it!"
) ? void (0) : __assert_fail ("(isa<PHINode>(EntryVal) || isa<TruncInst>(EntryVal)) && \"Expected either an induction phi-node or a truncate of it!\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9591, __extension__
__PRETTY_FUNCTION__))
;
9592
9593 // Construct the initial value of the vector IV in the vector loop preheader
9594 auto CurrIP = Builder.saveIP();
9595 Builder.SetInsertPoint(State.CFG.VectorPreHeader->getTerminator());
9596 if (isa<TruncInst>(EntryVal)) {
9597 assert(Start->getType()->isIntegerTy() &&(static_cast <bool> (Start->getType()->isIntegerTy
() && "Truncation requires an integer type") ? void (
0) : __assert_fail ("Start->getType()->isIntegerTy() && \"Truncation requires an integer type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9598, __extension__
__PRETTY_FUNCTION__))
9598 "Truncation requires an integer type")(static_cast <bool> (Start->getType()->isIntegerTy
() && "Truncation requires an integer type") ? void (
0) : __assert_fail ("Start->getType()->isIntegerTy() && \"Truncation requires an integer type\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9598, __extension__
__PRETTY_FUNCTION__))
;
9599 auto *TruncType = cast<IntegerType>(EntryVal->getType());
9600 Step = Builder.CreateTrunc(Step, TruncType);
9601 Start = Builder.CreateCast(Instruction::Trunc, Start, TruncType);
9602 }
9603
9604 Value *Zero = getSignedIntOrFpConstant(Start->getType(), 0);
9605 Value *SplatStart = Builder.CreateVectorSplat(State.VF, Start);
9606 Value *SteppedStart = getStepVector(
9607 SplatStart, Zero, Step, ID.getInductionOpcode(), State.VF, State.Builder);
9608
9609 // We create vector phi nodes for both integer and floating-point induction
9610 // variables. Here, we determine the kind of arithmetic we will perform.
9611 Instruction::BinaryOps AddOp;
9612 Instruction::BinaryOps MulOp;
9613 if (Step->getType()->isIntegerTy()) {
9614 AddOp = Instruction::Add;
9615 MulOp = Instruction::Mul;
9616 } else {
9617 AddOp = ID.getInductionOpcode();
9618 MulOp = Instruction::FMul;
9619 }
9620
9621 // Multiply the vectorization factor by the step using integer or
9622 // floating-point arithmetic as appropriate.
9623 Type *StepType = Step->getType();
9624 Value *RuntimeVF;
9625 if (Step->getType()->isFloatingPointTy())
9626 RuntimeVF = getRuntimeVFAsFloat(Builder, StepType, State.VF);
9627 else
9628 RuntimeVF = getRuntimeVF(Builder, StepType, State.VF);
9629 Value *Mul = Builder.CreateBinOp(MulOp, Step, RuntimeVF);
9630
9631 // Create a vector splat to use in the induction update.
9632 //
9633 // FIXME: If the step is non-constant, we create the vector splat with
9634 // IRBuilder. IRBuilder can constant-fold the multiply, but it doesn't
9635 // handle a constant vector splat.
9636 Value *SplatVF = isa<Constant>(Mul)
9637 ? ConstantVector::getSplat(State.VF, cast<Constant>(Mul))
9638 : Builder.CreateVectorSplat(State.VF, Mul);
9639 Builder.restoreIP(CurrIP);
9640
9641 // We may need to add the step a number of times, depending on the unroll
9642 // factor. The last of those goes into the PHI.
9643 PHINode *VecInd = PHINode::Create(SteppedStart->getType(), 2, "vec.ind",
9644 &*State.CFG.PrevBB->getFirstInsertionPt());
9645 VecInd->setDebugLoc(EntryVal->getDebugLoc());
9646 Instruction *LastInduction = VecInd;
9647 for (unsigned Part = 0; Part < State.UF; ++Part) {
9648 State.set(this, LastInduction, Part);
9649
9650 if (isa<TruncInst>(EntryVal))
9651 State.ILV->addMetadata(LastInduction, EntryVal);
9652
9653 LastInduction = cast<Instruction>(
9654 Builder.CreateBinOp(AddOp, LastInduction, SplatVF, "step.add"));
9655 LastInduction->setDebugLoc(EntryVal->getDebugLoc());
9656 }
9657
9658 // Move the last step to the end of the latch block. This ensures consistent
9659 // placement of all induction updates.
9660 auto *LoopVectorLatch =
9661 State.LI->getLoopFor(State.CFG.PrevBB)->getLoopLatch();
9662 auto *Br = cast<BranchInst>(LoopVectorLatch->getTerminator());
9663 LastInduction->moveBefore(Br);
9664 LastInduction->setName("vec.ind.next");
9665
9666 VecInd->addIncoming(SteppedStart, State.CFG.VectorPreHeader);
9667 VecInd->addIncoming(LastInduction, LoopVectorLatch);
9668}
9669
9670void VPScalarIVStepsRecipe::execute(VPTransformState &State) {
9671 assert(!State.Instance && "VPScalarIVStepsRecipe being replicated.")(static_cast <bool> (!State.Instance && "VPScalarIVStepsRecipe being replicated."
) ? void (0) : __assert_fail ("!State.Instance && \"VPScalarIVStepsRecipe being replicated.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9671, __extension__
__PRETTY_FUNCTION__))
;
9672
9673 // Fast-math-flags propagate from the original induction instruction.
9674 IRBuilder<>::FastMathFlagGuard FMFG(State.Builder);
9675 if (IndDesc.getInductionBinOp() &&
9676 isa<FPMathOperator>(IndDesc.getInductionBinOp()))
9677 State.Builder.setFastMathFlags(
9678 IndDesc.getInductionBinOp()->getFastMathFlags());
9679
9680 Value *Step = State.get(getStepValue(), VPIteration(0, 0));
9681 auto CreateScalarIV = [&](Value *&Step) -> Value * {
9682 Value *ScalarIV = State.get(getCanonicalIV(), VPIteration(0, 0));
9683 auto *CanonicalIV = State.get(getParent()->getPlan()->getCanonicalIV(), 0);
9684 if (!isCanonical() || CanonicalIV->getType() != Ty) {
9685 ScalarIV =
9686 Ty->isIntegerTy()
9687 ? State.Builder.CreateSExtOrTrunc(ScalarIV, Ty)
9688 : State.Builder.CreateCast(Instruction::SIToFP, ScalarIV, Ty);
9689 ScalarIV = emitTransformedIndex(State.Builder, ScalarIV,
9690 getStartValue()->getLiveInIRValue(), Step,
9691 IndDesc);
9692 ScalarIV->setName("offset.idx");
9693 }
9694 if (TruncToTy) {
9695 assert(Step->getType()->isIntegerTy() &&(static_cast <bool> (Step->getType()->isIntegerTy
() && "Truncation requires an integer step") ? void (
0) : __assert_fail ("Step->getType()->isIntegerTy() && \"Truncation requires an integer step\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9696, __extension__
__PRETTY_FUNCTION__))
9696 "Truncation requires an integer step")(static_cast <bool> (Step->getType()->isIntegerTy
() && "Truncation requires an integer step") ? void (
0) : __assert_fail ("Step->getType()->isIntegerTy() && \"Truncation requires an integer step\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9696, __extension__
__PRETTY_FUNCTION__))
;
9697 ScalarIV = State.Builder.CreateTrunc(ScalarIV, TruncToTy);
9698 Step = State.Builder.CreateTrunc(Step, TruncToTy);
9699 }
9700 return ScalarIV;
9701 };
9702
9703 Value *ScalarIV = CreateScalarIV(Step);
9704 if (State.VF.isVector()) {
9705 buildScalarSteps(ScalarIV, Step, IndDesc, this, State);
9706 return;
9707 }
9708
9709 for (unsigned Part = 0; Part < State.UF; ++Part) {
9710 assert(!State.VF.isScalable() && "scalable vectors not yet supported.")(static_cast <bool> (!State.VF.isScalable() && "scalable vectors not yet supported."
) ? void (0) : __assert_fail ("!State.VF.isScalable() && \"scalable vectors not yet supported.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9710, __extension__
__PRETTY_FUNCTION__))
;
9711 Value *EntryPart;
9712 if (Step->getType()->isFloatingPointTy()) {
9713 Value *StartIdx =
9714 getRuntimeVFAsFloat(State.Builder, Step->getType(), State.VF * Part);
9715 // Floating-point operations inherit FMF via the builder's flags.
9716 Value *MulOp = State.Builder.CreateFMul(StartIdx, Step);
9717 EntryPart = State.Builder.CreateBinOp(IndDesc.getInductionOpcode(),
9718 ScalarIV, MulOp);
9719 } else {
9720 Value *StartIdx =
9721 getRuntimeVF(State.Builder, Step->getType(), State.VF * Part);
9722 EntryPart = State.Builder.CreateAdd(
9723 ScalarIV, State.Builder.CreateMul(StartIdx, Step), "induction");
9724 }
9725 State.set(this, EntryPart, Part);
9726 }
9727}
9728
9729void VPWidenPHIRecipe::execute(VPTransformState &State) {
9730 State.ILV->widenPHIInstruction(cast<PHINode>(getUnderlyingValue()), this,
9731 State);
9732}
9733
9734void VPBlendRecipe::execute(VPTransformState &State) {
9735 State.ILV->setDebugLocFromInst(Phi, &State.Builder);
9736 // We know that all PHIs in non-header blocks are converted into
9737 // selects, so we don't have to worry about the insertion order and we
9738 // can just use the builder.
9739 // At this point we generate the predication tree. There may be
9740 // duplications since this is a simple recursive scan, but future
9741 // optimizations will clean it up.
9742
9743 unsigned NumIncoming = getNumIncomingValues();
9744
9745 // Generate a sequence of selects of the form:
9746 // SELECT(Mask3, In3,
9747 // SELECT(Mask2, In2,
9748 // SELECT(Mask1, In1,
9749 // In0)))
9750 // Note that Mask0 is never used: lanes for which no path reaches this phi and
9751 // are essentially undef are taken from In0.
9752 InnerLoopVectorizer::VectorParts Entry(State.UF);
9753 for (unsigned In = 0; In < NumIncoming; ++In) {
9754 for (unsigned Part = 0; Part < State.UF; ++Part) {
9755 // We might have single edge PHIs (blocks) - use an identity
9756 // 'select' for the first PHI operand.
9757 Value *In0 = State.get(getIncomingValue(In), Part);
9758 if (In == 0)
9759 Entry[Part] = In0; // Initialize with the first incoming value.
9760 else {
9761 // Select between the current value and the previous incoming edge
9762 // based on the incoming mask.
9763 Value *Cond = State.get(getMask(In), Part);
9764 Entry[Part] =
9765 State.Builder.CreateSelect(Cond, In0, Entry[Part], "predphi");
9766 }
9767 }
9768 }
9769 for (unsigned Part = 0; Part < State.UF; ++Part)
9770 State.set(this, Entry[Part], Part);
9771}
9772
9773void VPInterleaveRecipe::execute(VPTransformState &State) {
9774 assert(!State.Instance && "Interleave group being replicated.")(static_cast <bool> (!State.Instance && "Interleave group being replicated."
) ? void (0) : __assert_fail ("!State.Instance && \"Interleave group being replicated.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9774, __extension__
__PRETTY_FUNCTION__))
;
9775 State.ILV->vectorizeInterleaveGroup(IG, definedValues(), State, getAddr(),
9776 getStoredValues(), getMask());
9777}
9778
9779void VPReductionRecipe::execute(VPTransformState &State) {
9780 assert(!State.Instance && "Reduction being replicated.")(static_cast <bool> (!State.Instance && "Reduction being replicated."
) ? void (0) : __assert_fail ("!State.Instance && \"Reduction being replicated.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9780, __extension__
__PRETTY_FUNCTION__))
;
9781 Value *PrevInChain = State.get(getChainOp(), 0);
9782 RecurKind Kind = RdxDesc->getRecurrenceKind();
9783 bool IsOrdered = State.ILV->useOrderedReductions(*RdxDesc);
9784 // Propagate the fast-math flags carried by the underlying instruction.
9785 IRBuilderBase::FastMathFlagGuard FMFGuard(State.Builder);
9786 State.Builder.setFastMathFlags(RdxDesc->getFastMathFlags());
9787 for (unsigned Part = 0; Part < State.UF; ++Part) {
9788 Value *NewVecOp = State.get(getVecOp(), Part);
9789 if (VPValue *Cond = getCondOp()) {
9790 Value *NewCond = State.get(Cond, Part);
9791 VectorType *VecTy = cast<VectorType>(NewVecOp->getType());
9792 Value *Iden = RdxDesc->getRecurrenceIdentity(
9793 Kind, VecTy->getElementType(), RdxDesc->getFastMathFlags());
9794 Value *IdenVec =
9795 State.Builder.CreateVectorSplat(VecTy->getElementCount(), Iden);
9796 Value *Select = State.Builder.CreateSelect(NewCond, NewVecOp, IdenVec);
9797 NewVecOp = Select;
9798 }
9799 Value *NewRed;
9800 Value *NextInChain;
9801 if (IsOrdered) {
9802 if (State.VF.isVector())
9803 NewRed = createOrderedReduction(State.Builder, *RdxDesc, NewVecOp,
9804 PrevInChain);
9805 else
9806 NewRed = State.Builder.CreateBinOp(
9807 (Instruction::BinaryOps)RdxDesc->getOpcode(Kind), PrevInChain,
9808 NewVecOp);
9809 PrevInChain = NewRed;
9810 } else {
9811 PrevInChain = State.get(getChainOp(), Part);
9812 NewRed = createTargetReduction(State.Builder, TTI, *RdxDesc, NewVecOp);
9813 }
9814 if (RecurrenceDescriptor::isMinMaxRecurrenceKind(Kind)) {
9815 NextInChain =
9816 createMinMaxOp(State.Builder, RdxDesc->getRecurrenceKind(),
9817 NewRed, PrevInChain);
9818 } else if (IsOrdered)
9819 NextInChain = NewRed;
9820 else
9821 NextInChain = State.Builder.CreateBinOp(
9822 (Instruction::BinaryOps)RdxDesc->getOpcode(Kind), NewRed,
9823 PrevInChain);
9824 State.set(this, NextInChain, Part);
9825 }
9826}
9827
9828void VPReplicateRecipe::execute(VPTransformState &State) {
9829 if (State.Instance) { // Generate a single instance.
9830 assert(!State.VF.isScalable() && "Can't scalarize a scalable vector")(static_cast <bool> (!State.VF.isScalable() && "Can't scalarize a scalable vector"
) ? void (0) : __assert_fail ("!State.VF.isScalable() && \"Can't scalarize a scalable vector\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9830, __extension__
__PRETTY_FUNCTION__))
;
9831 State.ILV->scalarizeInstruction(getUnderlyingInstr(), this, *State.Instance,
9832 IsPredicated, State);
9833 // Insert scalar instance packing it into a vector.
9834 if (AlsoPack && State.VF.isVector()) {
9835 // If we're constructing lane 0, initialize to start from poison.
9836 if (State.Instance->Lane.isFirstLane()) {
9837 assert(!State.VF.isScalable() && "VF is assumed to be non scalable.")(static_cast <bool> (!State.VF.isScalable() && "VF is assumed to be non scalable."
) ? void (0) : __assert_fail ("!State.VF.isScalable() && \"VF is assumed to be non scalable.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9837, __extension__
__PRETTY_FUNCTION__))
;
9838 Value *Poison = PoisonValue::get(
9839 VectorType::get(getUnderlyingValue()->getType(), State.VF));
9840 State.set(this, Poison, State.Instance->Part);
9841 }
9842 State.ILV->packScalarIntoVectorValue(this, *State.Instance, State);
9843 }
9844 return;
9845 }
9846
9847 // Generate scalar instances for all VF lanes of all UF parts, unless the
9848 // instruction is uniform inwhich case generate only the first lane for each
9849 // of the UF parts.
9850 unsigned EndLane = IsUniform ? 1 : State.VF.getKnownMinValue();
9851 assert((!State.VF.isScalable() || IsUniform) &&(static_cast <bool> ((!State.VF.isScalable() || IsUniform
) && "Can't scalarize a scalable vector") ? void (0) :
__assert_fail ("(!State.VF.isScalable() || IsUniform) && \"Can't scalarize a scalable vector\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9852, __extension__
__PRETTY_FUNCTION__))
9852 "Can't scalarize a scalable vector")(static_cast <bool> ((!State.VF.isScalable() || IsUniform
) && "Can't scalarize a scalable vector") ? void (0) :
__assert_fail ("(!State.VF.isScalable() || IsUniform) && \"Can't scalarize a scalable vector\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9852, __extension__
__PRETTY_FUNCTION__))
;
9853 for (unsigned Part = 0; Part < State.UF; ++Part)
9854 for (unsigned Lane = 0; Lane < EndLane; ++Lane)
9855 State.ILV->scalarizeInstruction(getUnderlyingInstr(), this,
9856 VPIteration(Part, Lane), IsPredicated,
9857 State);
9858}
9859
9860void VPBranchOnMaskRecipe::execute(VPTransformState &State) {
9861 assert(State.Instance && "Branch on Mask works only on single instance.")(static_cast <bool> (State.Instance && "Branch on Mask works only on single instance."
) ? void (0) : __assert_fail ("State.Instance && \"Branch on Mask works only on single instance.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9861, __extension__
__PRETTY_FUNCTION__))
;
9862
9863 unsigned Part = State.Instance->Part;
9864 unsigned Lane = State.Instance->Lane.getKnownLane();
9865
9866 Value *ConditionBit = nullptr;
9867 VPValue *BlockInMask = getMask();
9868 if (BlockInMask) {
9869 ConditionBit = State.get(BlockInMask, Part);
9870 if (ConditionBit->getType()->isVectorTy())
9871 ConditionBit = State.Builder.CreateExtractElement(
9872 ConditionBit, State.Builder.getInt32(Lane));
9873 } else // Block in mask is all-one.
9874 ConditionBit = State.Builder.getTrue();
9875
9876 // Replace the temporary unreachable terminator with a new conditional branch,
9877 // whose two destinations will be set later when they are created.
9878 auto *CurrentTerminator = State.CFG.PrevBB->getTerminator();
9879 assert(isa<UnreachableInst>(CurrentTerminator) &&(static_cast <bool> (isa<UnreachableInst>(CurrentTerminator
) && "Expected to replace unreachable terminator with conditional branch."
) ? void (0) : __assert_fail ("isa<UnreachableInst>(CurrentTerminator) && \"Expected to replace unreachable terminator with conditional branch.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9880, __extension__
__PRETTY_FUNCTION__))
9880 "Expected to replace unreachable terminator with conditional branch.")(static_cast <bool> (isa<UnreachableInst>(CurrentTerminator
) && "Expected to replace unreachable terminator with conditional branch."
) ? void (0) : __assert_fail ("isa<UnreachableInst>(CurrentTerminator) && \"Expected to replace unreachable terminator with conditional branch.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9880, __extension__
__PRETTY_FUNCTION__))
;
9881 auto *CondBr = BranchInst::Create(State.CFG.PrevBB, nullptr, ConditionBit);
9882 CondBr->setSuccessor(0, nullptr);
9883 ReplaceInstWithInst(CurrentTerminator, CondBr);
9884}
9885
9886void VPPredInstPHIRecipe::execute(VPTransformState &State) {
9887 assert(State.Instance && "Predicated instruction PHI works per instance.")(static_cast <bool> (State.Instance && "Predicated instruction PHI works per instance."
) ? void (0) : __assert_fail ("State.Instance && \"Predicated instruction PHI works per instance.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9887, __extension__
__PRETTY_FUNCTION__))
;
9888 Instruction *ScalarPredInst =
9889 cast<Instruction>(State.get(getOperand(0), *State.Instance));
9890 BasicBlock *PredicatedBB = ScalarPredInst->getParent();
9891 BasicBlock *PredicatingBB = PredicatedBB->getSinglePredecessor();
9892 assert(PredicatingBB && "Predicated block has no single predecessor.")(static_cast <bool> (PredicatingBB && "Predicated block has no single predecessor."
) ? void (0) : __assert_fail ("PredicatingBB && \"Predicated block has no single predecessor.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9892, __extension__
__PRETTY_FUNCTION__))
;
9893 assert(isa<VPReplicateRecipe>(getOperand(0)) &&(static_cast <bool> (isa<VPReplicateRecipe>(getOperand
(0)) && "operand must be VPReplicateRecipe") ? void (
0) : __assert_fail ("isa<VPReplicateRecipe>(getOperand(0)) && \"operand must be VPReplicateRecipe\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9894, __extension__
__PRETTY_FUNCTION__))
9894 "operand must be VPReplicateRecipe")(static_cast <bool> (isa<VPReplicateRecipe>(getOperand
(0)) && "operand must be VPReplicateRecipe") ? void (
0) : __assert_fail ("isa<VPReplicateRecipe>(getOperand(0)) && \"operand must be VPReplicateRecipe\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9894, __extension__
__PRETTY_FUNCTION__))
;
9895
9896 // By current pack/unpack logic we need to generate only a single phi node: if
9897 // a vector value for the predicated instruction exists at this point it means
9898 // the instruction has vector users only, and a phi for the vector value is
9899 // needed. In this case the recipe of the predicated instruction is marked to
9900 // also do that packing, thereby "hoisting" the insert-element sequence.
9901 // Otherwise, a phi node for the scalar value is needed.
9902 unsigned Part = State.Instance->Part;
9903 if (State.hasVectorValue(getOperand(0), Part)) {
9904 Value *VectorValue = State.get(getOperand(0), Part);
9905 InsertElementInst *IEI = cast<InsertElementInst>(VectorValue);
9906 PHINode *VPhi = State.Builder.CreatePHI(IEI->getType(), 2);
9907 VPhi->addIncoming(IEI->getOperand(0), PredicatingBB); // Unmodified vector.
9908 VPhi->addIncoming(IEI, PredicatedBB); // New vector with inserted element.
9909 if (State.hasVectorValue(this, Part))
9910 State.reset(this, VPhi, Part);
9911 else
9912 State.set(this, VPhi, Part);
9913 // NOTE: Currently we need to update the value of the operand, so the next
9914 // predicated iteration inserts its generated value in the correct vector.
9915 State.reset(getOperand(0), VPhi, Part);
9916 } else {
9917 Type *PredInstType = getOperand(0)->getUnderlyingValue()->getType();
9918 PHINode *Phi = State.Builder.CreatePHI(PredInstType, 2);
9919 Phi->addIncoming(PoisonValue::get(ScalarPredInst->getType()),
9920 PredicatingBB);
9921 Phi->addIncoming(ScalarPredInst, PredicatedBB);
9922 if (State.hasScalarValue(this, *State.Instance))
9923 State.reset(this, Phi, *State.Instance);
9924 else
9925 State.set(this, Phi, *State.Instance);
9926 // NOTE: Currently we need to update the value of the operand, so the next
9927 // predicated iteration inserts its generated value in the correct vector.
9928 State.reset(getOperand(0), Phi, *State.Instance);
9929 }
9930}
9931
9932void VPWidenMemoryInstructionRecipe::execute(VPTransformState &State) {
9933 VPValue *StoredValue = isStore() ? getStoredValue() : nullptr;
9934
9935 // Attempt to issue a wide load.
9936 LoadInst *LI = dyn_cast<LoadInst>(&Ingredient);
9937 StoreInst *SI = dyn_cast<StoreInst>(&Ingredient);
9938
9939 assert((LI || SI) && "Invalid Load/Store instruction")(static_cast <bool> ((LI || SI) && "Invalid Load/Store instruction"
) ? void (0) : __assert_fail ("(LI || SI) && \"Invalid Load/Store instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9939, __extension__
__PRETTY_FUNCTION__))
;
9940 assert((!SI || StoredValue) && "No stored value provided for widened store")(static_cast <bool> ((!SI || StoredValue) && "No stored value provided for widened store"
) ? void (0) : __assert_fail ("(!SI || StoredValue) && \"No stored value provided for widened store\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9940, __extension__
__PRETTY_FUNCTION__))
;
9941 assert((!LI || !StoredValue) && "Stored value provided for widened load")(static_cast <bool> ((!LI || !StoredValue) && "Stored value provided for widened load"
) ? void (0) : __assert_fail ("(!LI || !StoredValue) && \"Stored value provided for widened load\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 9941, __extension__
__PRETTY_FUNCTION__))
;
9942
9943 Type *ScalarDataTy = getLoadStoreType(&Ingredient);
9944
9945 auto *DataTy = VectorType::get(ScalarDataTy, State.VF);
9946 const Align Alignment = getLoadStoreAlignment(&Ingredient);
9947 bool CreateGatherScatter = !Consecutive;
9948
9949 auto &Builder = State.Builder;
9950 InnerLoopVectorizer::VectorParts BlockInMaskParts(State.UF);
9951 bool isMaskRequired = getMask();
9952 if (isMaskRequired)
9953 for (unsigned Part = 0; Part < State.UF; ++Part)
9954 BlockInMaskParts[Part] = State.get(getMask(), Part);
9955
9956 const auto CreateVecPtr = [&](unsigned Part, Value *Ptr) -> Value * {
9957 // Calculate the pointer for the specific unroll-part.
9958 GetElementPtrInst *PartPtr = nullptr;
9959
9960 bool InBounds = false;
9961 if (auto *gep = dyn_cast<GetElementPtrInst>(Ptr->stripPointerCasts()))
9962 InBounds = gep->isInBounds();
9963 if (Reverse) {
9964 // If the address is consecutive but reversed, then the
9965 // wide store needs to start at the last vector element.
9966 // RunTimeVF = VScale * VF.getKnownMinValue()
9967 // For fixed-width VScale is 1, then RunTimeVF = VF.getKnownMinValue()
9968 Value *RunTimeVF = getRuntimeVF(Builder, Builder.getInt32Ty(), State.VF);
9969 // NumElt = -Part * RunTimeVF
9970 Value *NumElt = Builder.CreateMul(Builder.getInt32(-Part), RunTimeVF);
9971 // LastLane = 1 - RunTimeVF
9972 Value *LastLane = Builder.CreateSub(Builder.getInt32(1), RunTimeVF);
9973 PartPtr =
9974 cast<GetElementPtrInst>(Builder.CreateGEP(ScalarDataTy, Ptr, NumElt));
9975 PartPtr->setIsInBounds(InBounds);
9976 PartPtr = cast<GetElementPtrInst>(
9977 Builder.CreateGEP(ScalarDataTy, PartPtr, LastLane));
9978 PartPtr->setIsInBounds(InBounds);
9979 if (isMaskRequired) // Reverse of a null all-one mask is a null mask.
9980 BlockInMaskParts[Part] =
9981 Builder.CreateVectorReverse(BlockInMaskParts[Part], "reverse");
9982 } else {
9983 Value *Increment =
9984 createStepForVF(Builder, Builder.getInt32Ty(), State.VF, Part);
9985 PartPtr = cast<GetElementPtrInst>(
9986 Builder.CreateGEP(ScalarDataTy, Ptr, Increment));
9987 PartPtr->setIsInBounds(InBounds);
9988 }
9989
9990 unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace();
9991 return Builder.CreateBitCast(PartPtr, DataTy->getPointerTo(AddressSpace));
9992 };
9993
9994 // Handle Stores:
9995 if (SI) {
9996 State.ILV->setDebugLocFromInst(SI);
9997
9998 for (unsigned Part = 0; Part < State.UF; ++Part) {
9999 Instruction *NewSI = nullptr;
10000 Value *StoredVal = State.get(StoredValue, Part);
10001 if (CreateGatherScatter) {
10002 Value *MaskPart = isMaskRequired ? BlockInMaskParts[Part] : nullptr;
10003 Value *VectorGep = State.get(getAddr(), Part);
10004 NewSI = Builder.CreateMaskedScatter(StoredVal, VectorGep, Alignment,
10005 MaskPart);
10006 } else {
10007 if (Reverse) {
10008 // If we store to reverse consecutive memory locations, then we need
10009 // to reverse the order of elements in the stored value.
10010 StoredVal = Builder.CreateVectorReverse(StoredVal, "reverse");
10011 // We don't want to update the value in the map as it might be used in
10012 // another expression. So don't call resetVectorValue(StoredVal).
10013 }
10014 auto *VecPtr =
10015 CreateVecPtr(Part, State.get(getAddr(), VPIteration(0, 0)));
10016 if (isMaskRequired)
10017 NewSI = Builder.CreateMaskedStore(StoredVal, VecPtr, Alignment,
10018 BlockInMaskParts[Part]);
10019 else
10020 NewSI = Builder.CreateAlignedStore(StoredVal, VecPtr, Alignment);
10021 }
10022 State.ILV->addMetadata(NewSI, SI);
10023 }
10024 return;
10025 }
10026
10027 // Handle loads.
10028 assert(LI && "Must have a load instruction")(static_cast <bool> (LI && "Must have a load instruction"
) ? void (0) : __assert_fail ("LI && \"Must have a load instruction\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10028, __extension__
__PRETTY_FUNCTION__))
;
10029 State.ILV->setDebugLocFromInst(LI);
10030 for (unsigned Part = 0; Part < State.UF; ++Part) {
10031 Value *NewLI;
10032 if (CreateGatherScatter) {
10033 Value *MaskPart = isMaskRequired ? BlockInMaskParts[Part] : nullptr;
10034 Value *VectorGep = State.get(getAddr(), Part);
10035 NewLI = Builder.CreateMaskedGather(DataTy, VectorGep, Alignment, MaskPart,
10036 nullptr, "wide.masked.gather");
10037 State.ILV->addMetadata(NewLI, LI);
10038 } else {
10039 auto *VecPtr =
10040 CreateVecPtr(Part, State.get(getAddr(), VPIteration(0, 0)));
10041 if (isMaskRequired)
10042 NewLI = Builder.CreateMaskedLoad(
10043 DataTy, VecPtr, Alignment, BlockInMaskParts[Part],
10044 PoisonValue::get(DataTy), "wide.masked.load");
10045 else
10046 NewLI =
10047 Builder.CreateAlignedLoad(DataTy, VecPtr, Alignment, "wide.load");
10048
10049 // Add metadata to the load, but setVectorValue to the reverse shuffle.
10050 State.ILV->addMetadata(NewLI, LI);
10051 if (Reverse)
10052 NewLI = Builder.CreateVectorReverse(NewLI, "reverse");
10053 }
10054
10055 State.set(this, NewLI, Part);
10056 }
10057}
10058
10059// Determine how to lower the scalar epilogue, which depends on 1) optimising
10060// for minimum code-size, 2) predicate compiler options, 3) loop hints forcing
10061// predication, and 4) a TTI hook that analyses whether the loop is suitable
10062// for predication.
10063static ScalarEpilogueLowering getScalarEpilogueLowering(
10064 Function *F, Loop *L, LoopVectorizeHints &Hints, ProfileSummaryInfo *PSI,
10065 BlockFrequencyInfo *BFI, TargetTransformInfo *TTI, TargetLibraryInfo *TLI,
10066 AssumptionCache *AC, LoopInfo *LI, ScalarEvolution *SE, DominatorTree *DT,
10067 LoopVectorizationLegality &LVL) {
10068 // 1) OptSize takes precedence over all other options, i.e. if this is set,
10069 // don't look at hints or options, and don't request a scalar epilogue.
10070 // (For PGSO, as shouldOptimizeForSize isn't currently accessible from
10071 // LoopAccessInfo (due to code dependency and not being able to reliably get
10072 // PSI/BFI from a loop analysis under NPM), we cannot suppress the collection
10073 // of strides in LoopAccessInfo::analyzeLoop() and vectorize without
10074 // versioning when the vectorization is forced, unlike hasOptSize. So revert
10075 // back to the old way and vectorize with versioning when forced. See D81345.)
10076 if (F->hasOptSize() || (llvm::shouldOptimizeForSize(L->getHeader(), PSI, BFI,
10077 PGSOQueryType::IRPass) &&
10078 Hints.getForce() != LoopVectorizeHints::FK_Enabled))
10079 return CM_ScalarEpilogueNotAllowedOptSize;
10080
10081 // 2) If set, obey the directives
10082 if (PreferPredicateOverEpilogue.getNumOccurrences()) {
10083 switch (PreferPredicateOverEpilogue) {
10084 case PreferPredicateTy::ScalarEpilogue:
10085 return CM_ScalarEpilogueAllowed;
10086 case PreferPredicateTy::PredicateElseScalarEpilogue:
10087 return CM_ScalarEpilogueNotNeededUsePredicate;
10088 case PreferPredicateTy::PredicateOrDontVectorize:
10089 return CM_ScalarEpilogueNotAllowedUsePredicate;
10090 };
10091 }
10092
10093 // 3) If set, obey the hints
10094 switch (Hints.getPredicate()) {
10095 case LoopVectorizeHints::FK_Enabled:
10096 return CM_ScalarEpilogueNotNeededUsePredicate;
10097 case LoopVectorizeHints::FK_Disabled:
10098 return CM_ScalarEpilogueAllowed;
10099 };
10100
10101 // 4) if the TTI hook indicates this is profitable, request predication.
10102 if (TTI->preferPredicateOverEpilogue(L, LI, *SE, *AC, TLI, DT,
10103 LVL.getLAI()))
10104 return CM_ScalarEpilogueNotNeededUsePredicate;
10105
10106 return CM_ScalarEpilogueAllowed;
10107}
10108
10109Value *VPTransformState::get(VPValue *Def, unsigned Part) {
10110 // If Values have been set for this Def return the one relevant for \p Part.
10111 if (hasVectorValue(Def, Part))
10112 return Data.PerPartOutput[Def][Part];
10113
10114 if (!hasScalarValue(Def, {Part, 0})) {
10115 Value *IRV = Def->getLiveInIRValue();
10116 Value *B = ILV->getBroadcastInstrs(IRV);
10117 set(Def, B, Part);
10118 return B;
10119 }
10120
10121 Value *ScalarValue = get(Def, {Part, 0});
10122 // If we aren't vectorizing, we can just copy the scalar map values over
10123 // to the vector map.
10124 if (VF.isScalar()) {
10125 set(Def, ScalarValue, Part);
10126 return ScalarValue;
10127 }
10128
10129 auto *RepR = dyn_cast<VPReplicateRecipe>(Def);
10130 bool IsUniform = RepR && RepR->isUniform();
10131
10132 unsigned LastLane = IsUniform ? 0 : VF.getKnownMinValue() - 1;
10133 // Check if there is a scalar value for the selected lane.
10134 if (!hasScalarValue(Def, {Part, LastLane})) {
10135 // At the moment, VPWidenIntOrFpInductionRecipes can also be uniform.
10136 assert((isa<VPWidenIntOrFpInductionRecipe>(Def->getDef()) ||(static_cast <bool> ((isa<VPWidenIntOrFpInductionRecipe
>(Def->getDef()) || isa<VPScalarIVStepsRecipe>(Def
->getDef())) && "unexpected recipe found to be invariant"
) ? void (0) : __assert_fail ("(isa<VPWidenIntOrFpInductionRecipe>(Def->getDef()) || isa<VPScalarIVStepsRecipe>(Def->getDef())) && \"unexpected recipe found to be invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10138, __extension__
__PRETTY_FUNCTION__))
10137 isa<VPScalarIVStepsRecipe>(Def->getDef())) &&(static_cast <bool> ((isa<VPWidenIntOrFpInductionRecipe
>(Def->getDef()) || isa<VPScalarIVStepsRecipe>(Def
->getDef())) && "unexpected recipe found to be invariant"
) ? void (0) : __assert_fail ("(isa<VPWidenIntOrFpInductionRecipe>(Def->getDef()) || isa<VPScalarIVStepsRecipe>(Def->getDef())) && \"unexpected recipe found to be invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10138, __extension__
__PRETTY_FUNCTION__))
10138 "unexpected recipe found to be invariant")(static_cast <bool> ((isa<VPWidenIntOrFpInductionRecipe
>(Def->getDef()) || isa<VPScalarIVStepsRecipe>(Def
->getDef())) && "unexpected recipe found to be invariant"
) ? void (0) : __assert_fail ("(isa<VPWidenIntOrFpInductionRecipe>(Def->getDef()) || isa<VPScalarIVStepsRecipe>(Def->getDef())) && \"unexpected recipe found to be invariant\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10138, __extension__
__PRETTY_FUNCTION__))
;
10139 IsUniform = true;
10140 LastLane = 0;
10141 }
10142
10143 auto *LastInst = cast<Instruction>(get(Def, {Part, LastLane}));
10144 // Set the insert point after the last scalarized instruction or after the
10145 // last PHI, if LastInst is a PHI. This ensures the insertelement sequence
10146 // will directly follow the scalar definitions.
10147 auto OldIP = Builder.saveIP();
10148 auto NewIP =
10149 isa<PHINode>(LastInst)
10150 ? BasicBlock::iterator(LastInst->getParent()->getFirstNonPHI())
10151 : std::next(BasicBlock::iterator(LastInst));
10152 Builder.SetInsertPoint(&*NewIP);
10153
10154 // However, if we are vectorizing, we need to construct the vector values.
10155 // If the value is known to be uniform after vectorization, we can just
10156 // broadcast the scalar value corresponding to lane zero for each unroll
10157 // iteration. Otherwise, we construct the vector values using
10158 // insertelement instructions. Since the resulting vectors are stored in
10159 // State, we will only generate the insertelements once.
10160 Value *VectorValue = nullptr;
10161 if (IsUniform) {
10162 VectorValue = ILV->getBroadcastInstrs(ScalarValue);
10163 set(Def, VectorValue, Part);
10164 } else {
10165 // Initialize packing with insertelements to start from undef.
10166 assert(!VF.isScalable() && "VF is assumed to be non scalable.")(static_cast <bool> (!VF.isScalable() && "VF is assumed to be non scalable."
) ? void (0) : __assert_fail ("!VF.isScalable() && \"VF is assumed to be non scalable.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10166, __extension__
__PRETTY_FUNCTION__))
;
10167 Value *Undef = PoisonValue::get(VectorType::get(LastInst->getType(), VF));
10168 set(Def, Undef, Part);
10169 for (unsigned Lane = 0; Lane < VF.getKnownMinValue(); ++Lane)
10170 ILV->packScalarIntoVectorValue(Def, {Part, Lane}, *this);
10171 VectorValue = get(Def, Part);
10172 }
10173 Builder.restoreIP(OldIP);
10174 return VectorValue;
10175}
10176
10177// Process the loop in the VPlan-native vectorization path. This path builds
10178// VPlan upfront in the vectorization pipeline, which allows to apply
10179// VPlan-to-VPlan transformations from the very beginning without modifying the
10180// input LLVM IR.
10181static bool processLoopInVPlanNativePath(
10182 Loop *L, PredicatedScalarEvolution &PSE, LoopInfo *LI, DominatorTree *DT,
10183 LoopVectorizationLegality *LVL, TargetTransformInfo *TTI,
10184 TargetLibraryInfo *TLI, DemandedBits *DB, AssumptionCache *AC,
10185 OptimizationRemarkEmitter *ORE, BlockFrequencyInfo *BFI,
10186 ProfileSummaryInfo *PSI, LoopVectorizeHints &Hints,
10187 LoopVectorizationRequirements &Requirements) {
10188
10189 if (isa<SCEVCouldNotCompute>(PSE.getBackedgeTakenCount())) {
10190 LLVM_DEBUG(dbgs() << "LV: cannot compute the outer-loop trip count\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: cannot compute the outer-loop trip count\n"
; } } while (false)
;
10191 return false;
10192 }
10193 assert(EnableVPlanNativePath && "VPlan-native path is disabled.")(static_cast <bool> (EnableVPlanNativePath && "VPlan-native path is disabled."
) ? void (0) : __assert_fail ("EnableVPlanNativePath && \"VPlan-native path is disabled.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10193, __extension__
__PRETTY_FUNCTION__))
;
10194 Function *F = L->getHeader()->getParent();
10195 InterleavedAccessInfo IAI(PSE, L, DT, LI, LVL->getLAI());
10196
10197 ScalarEpilogueLowering SEL = getScalarEpilogueLowering(
10198 F, L, Hints, PSI, BFI, TTI, TLI, AC, LI, PSE.getSE(), DT, *LVL);
10199
10200 LoopVectorizationCostModel CM(SEL, L, PSE, LI, LVL, *TTI, TLI, DB, AC, ORE, F,
10201 &Hints, IAI);
10202 // Use the planner for outer loop vectorization.
10203 // TODO: CM is not used at this point inside the planner. Turn CM into an
10204 // optional argument if we don't need it in the future.
10205 LoopVectorizationPlanner LVP(L, LI, TLI, TTI, LVL, CM, IAI, PSE, Hints,
10206 Requirements, ORE);
10207
10208 // Get user vectorization factor.
10209 ElementCount UserVF = Hints.getWidth();
10210
10211 CM.collectElementTypesForWidening();
10212
10213 // Plan how to best vectorize, return the best VF and its cost.
10214 const VectorizationFactor VF = LVP.planInVPlanNativePath(UserVF);
10215
10216 // If we are stress testing VPlan builds, do not attempt to generate vector
10217 // code. Masked vector code generation support will follow soon.
10218 // Also, do not attempt to vectorize if no vector code will be produced.
10219 if (VPlanBuildStressTest || EnableVPlanPredication ||
10220 VectorizationFactor::Disabled() == VF)
10221 return false;
10222
10223 VPlan &BestPlan = LVP.getBestPlanFor(VF.Width);
10224
10225 {
10226 GeneratedRTChecks Checks(*PSE.getSE(), DT, LI,
10227 F->getParent()->getDataLayout());
10228 InnerLoopVectorizer LB(L, PSE, LI, DT, TLI, TTI, AC, ORE, VF.Width, 1, LVL,
10229 &CM, BFI, PSI, Checks);
10230 LLVM_DEBUG(dbgs() << "Vectorizing outer loop in \""do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "Vectorizing outer loop in \""
<< L->getHeader()->getParent()->getName() <<
"\"\n"; } } while (false)
10231 << L->getHeader()->getParent()->getName() << "\"\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "Vectorizing outer loop in \""
<< L->getHeader()->getParent()->getName() <<
"\"\n"; } } while (false)
;
10232 LVP.executePlan(VF.Width, 1, BestPlan, LB, DT);
10233 }
10234
10235 // Mark the loop as already vectorized to avoid vectorizing again.
10236 Hints.setAlreadyVectorized();
10237 assert(!verifyFunction(*L->getHeader()->getParent(), &dbgs()))(static_cast <bool> (!verifyFunction(*L->getHeader()
->getParent(), &dbgs())) ? void (0) : __assert_fail ("!verifyFunction(*L->getHeader()->getParent(), &dbgs())"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10237, __extension__
__PRETTY_FUNCTION__))
;
10238 return true;
10239}
10240
10241// Emit a remark if there are stores to floats that required a floating point
10242// extension. If the vectorized loop was generated with floating point there
10243// will be a performance penalty from the conversion overhead and the change in
10244// the vector width.
10245static void checkMixedPrecision(Loop *L, OptimizationRemarkEmitter *ORE) {
10246 SmallVector<Instruction *, 4> Worklist;
10247 for (BasicBlock *BB : L->getBlocks()) {
10248 for (Instruction &Inst : *BB) {
10249 if (auto *S = dyn_cast<StoreInst>(&Inst)) {
10250 if (S->getValueOperand()->getType()->isFloatTy())
10251 Worklist.push_back(S);
10252 }
10253 }
10254 }
10255
10256 // Traverse the floating point stores upwards searching, for floating point
10257 // conversions.
10258 SmallPtrSet<const Instruction *, 4> Visited;
10259 SmallPtrSet<const Instruction *, 4> EmittedRemark;
10260 while (!Worklist.empty()) {
10261 auto *I = Worklist.pop_back_val();
10262 if (!L->contains(I))
10263 continue;
10264 if (!Visited.insert(I).second)
10265 continue;
10266
10267 // Emit a remark if the floating point store required a floating
10268 // point conversion.
10269 // TODO: More work could be done to identify the root cause such as a
10270 // constant or a function return type and point the user to it.
10271 if (isa<FPExtInst>(I) && EmittedRemark.insert(I).second)
10272 ORE->emit([&]() {
10273 return OptimizationRemarkAnalysis(LV_NAME"loop-vectorize", "VectorMixedPrecision",
10274 I->getDebugLoc(), L->getHeader())
10275 << "floating point conversion changes vector width. "
10276 << "Mixed floating point precision requires an up/down "
10277 << "cast that will negatively impact performance.";
10278 });
10279
10280 for (Use &Op : I->operands())
10281 if (auto *OpI = dyn_cast<Instruction>(Op))
10282 Worklist.push_back(OpI);
10283 }
10284}
10285
10286LoopVectorizePass::LoopVectorizePass(LoopVectorizeOptions Opts)
10287 : InterleaveOnlyWhenForced(Opts.InterleaveOnlyWhenForced ||
10288 !EnableLoopInterleaving),
10289 VectorizeOnlyWhenForced(Opts.VectorizeOnlyWhenForced ||
10290 !EnableLoopVectorization) {}
10291
10292bool LoopVectorizePass::processLoop(Loop *L) {
10293 assert((EnableVPlanNativePath || L->isInnermost()) &&(static_cast <bool> ((EnableVPlanNativePath || L->isInnermost
()) && "VPlan-native path is not enabled. Only process inner loops."
) ? void (0) : __assert_fail ("(EnableVPlanNativePath || L->isInnermost()) && \"VPlan-native path is not enabled. Only process inner loops.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10294, __extension__
__PRETTY_FUNCTION__))
10294 "VPlan-native path is not enabled. Only process inner loops.")(static_cast <bool> ((EnableVPlanNativePath || L->isInnermost
()) && "VPlan-native path is not enabled. Only process inner loops."
) ? void (0) : __assert_fail ("(EnableVPlanNativePath || L->isInnermost()) && \"VPlan-native path is not enabled. Only process inner loops.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10294, __extension__
__PRETTY_FUNCTION__))
;
10295
10296#ifndef NDEBUG
10297 const std::string DebugLocStr = getDebugLocString(L);
10298#endif /* NDEBUG */
10299
10300 LLVM_DEBUG(dbgs() << "\nLV: Checking a loop in '"do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "\nLV: Checking a loop in '"
<< L->getHeader()->getParent()->getName() <<
"' from " << DebugLocStr << "\n"; } } while (false
)
10301 << L->getHeader()->getParent()->getName() << "' from "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "\nLV: Checking a loop in '"
<< L->getHeader()->getParent()->getName() <<
"' from " << DebugLocStr << "\n"; } } while (false
)
10302 << DebugLocStr << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "\nLV: Checking a loop in '"
<< L->getHeader()->getParent()->getName() <<
"' from " << DebugLocStr << "\n"; } } while (false
)
;
10303
10304 LoopVectorizeHints Hints(L, InterleaveOnlyWhenForced, *ORE, TTI);
10305
10306 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10307 dbgs() << "LV: Loop hints:"do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10308 << " force="do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10309 << (Hints.getForce() == LoopVectorizeHints::FK_Disableddo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10310 ? "disabled"do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10311 : (Hints.getForce() == LoopVectorizeHints::FK_Enableddo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10312 ? "enabled"do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10313 : "?"))do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10314 << " width=" << Hints.getWidth()do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
10315 << " interleave=" << Hints.getInterleave() << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints:" <<
" force=" << (Hints.getForce() == LoopVectorizeHints::
FK_Disabled ? "disabled" : (Hints.getForce() == LoopVectorizeHints
::FK_Enabled ? "enabled" : "?")) << " width=" << Hints
.getWidth() << " interleave=" << Hints.getInterleave
() << "\n"; } } while (false)
;
10316
10317 // Function containing loop
10318 Function *F = L->getHeader()->getParent();
10319
10320 // Looking at the diagnostic output is the only way to determine if a loop
10321 // was vectorized (other than looking at the IR or machine code), so it
10322 // is important to generate an optimization remark for each loop. Most of
10323 // these messages are generated as OptimizationRemarkAnalysis. Remarks
10324 // generated as OptimizationRemark and OptimizationRemarkMissed are
10325 // less verbose reporting vectorized loops and unvectorized loops that may
10326 // benefit from vectorization, respectively.
10327
10328 if (!Hints.allowVectorization(F, L, VectorizeOnlyWhenForced)) {
10329 LLVM_DEBUG(dbgs() << "LV: Loop hints prevent vectorization.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Loop hints prevent vectorization.\n"
; } } while (false)
;
10330 return false;
10331 }
10332
10333 PredicatedScalarEvolution PSE(*SE, *L);
10334
10335 // Check if it is legal to vectorize the loop.
10336 LoopVectorizationRequirements Requirements;
10337 LoopVectorizationLegality LVL(L, PSE, DT, TTI, TLI, AA, F, GetLAA, LI, ORE,
10338 &Requirements, &Hints, DB, AC, BFI, PSI);
10339 if (!LVL.canVectorize(EnableVPlanNativePath)) {
10340 LLVM_DEBUG(dbgs() << "LV: Not vectorizing: Cannot prove legality.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Not vectorizing: Cannot prove legality.\n"
; } } while (false)
;
10341 Hints.emitRemarkWithHints();
10342 return false;
10343 }
10344
10345 // Check the function attributes and profiles to find out if this function
10346 // should be optimized for size.
10347 ScalarEpilogueLowering SEL = getScalarEpilogueLowering(
10348 F, L, Hints, PSI, BFI, TTI, TLI, AC, LI, PSE.getSE(), DT, LVL);
10349
10350 // Entrance to the VPlan-native vectorization path. Outer loops are processed
10351 // here. They may require CFG and instruction level transformations before
10352 // even evaluating whether vectorization is profitable. Since we cannot modify
10353 // the incoming IR, we need to build VPlan upfront in the vectorization
10354 // pipeline.
10355 if (!L->isInnermost())
10356 return processLoopInVPlanNativePath(L, PSE, LI, DT, &LVL, TTI, TLI, DB, AC,
10357 ORE, BFI, PSI, Hints, Requirements);
10358
10359 assert(L->isInnermost() && "Inner loop expected.")(static_cast <bool> (L->isInnermost() && "Inner loop expected."
) ? void (0) : __assert_fail ("L->isInnermost() && \"Inner loop expected.\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10359, __extension__
__PRETTY_FUNCTION__))
;
10360
10361 // Check the loop for a trip count threshold: vectorize loops with a tiny trip
10362 // count by optimizing for size, to minimize overheads.
10363 auto ExpectedTC = getSmallBestKnownTC(*SE, L);
10364 if (ExpectedTC && *ExpectedTC < TinyTripCountVectorThreshold) {
10365 LLVM_DEBUG(dbgs() << "LV: Found a loop with a very small trip count. "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found a loop with a very small trip count. "
<< "This loop is worth vectorizing only if no scalar "
<< "iteration overheads are incurred."; } } while (false
)
10366 << "This loop is worth vectorizing only if no scalar "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found a loop with a very small trip count. "
<< "This loop is worth vectorizing only if no scalar "
<< "iteration overheads are incurred."; } } while (false
)
10367 << "iteration overheads are incurred.")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found a loop with a very small trip count. "
<< "This loop is worth vectorizing only if no scalar "
<< "iteration overheads are incurred."; } } while (false
)
;
10368 if (Hints.getForce() == LoopVectorizeHints::FK_Enabled)
10369 LLVM_DEBUG(dbgs() << " But vectorizing was explicitly forced.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << " But vectorizing was explicitly forced.\n"
; } } while (false)
;
10370 else {
10371 LLVM_DEBUG(dbgs() << "\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "\n"; } } while (false)
;
10372 SEL = CM_ScalarEpilogueNotAllowedLowTripLoop;
10373 }
10374 }
10375
10376 // Check the function attributes to see if implicit floats are allowed.
10377 // FIXME: This check doesn't seem possibly correct -- what if the loop is
10378 // an integer loop and the vector instructions selected are purely integer
10379 // vector instructions?
10380 if (F->hasFnAttribute(Attribute::NoImplicitFloat)) {
10381 reportVectorizationFailure(
10382 "Can't vectorize when the NoImplicitFloat attribute is used",
10383 "loop not vectorized due to NoImplicitFloat attribute",
10384 "NoImplicitFloat", ORE, L);
10385 Hints.emitRemarkWithHints();
10386 return false;
10387 }
10388
10389 // Check if the target supports potentially unsafe FP vectorization.
10390 // FIXME: Add a check for the type of safety issue (denormal, signaling)
10391 // for the target we're vectorizing for, to make sure none of the
10392 // additional fp-math flags can help.
10393 if (Hints.isPotentiallyUnsafe() &&
10394 TTI->isFPVectorizationPotentiallyUnsafe()) {
10395 reportVectorizationFailure(
10396 "Potentially unsafe FP op prevents vectorization",
10397 "loop not vectorized due to unsafe FP support.",
10398 "UnsafeFP", ORE, L);
10399 Hints.emitRemarkWithHints();
10400 return false;
10401 }
10402
10403 bool AllowOrderedReductions;
10404 // If the flag is set, use that instead and override the TTI behaviour.
10405 if (ForceOrderedReductions.getNumOccurrences() > 0)
10406 AllowOrderedReductions = ForceOrderedReductions;
10407 else
10408 AllowOrderedReductions = TTI->enableOrderedReductions();
10409 if (!LVL.canVectorizeFPMath(AllowOrderedReductions)) {
10410 ORE->emit([&]() {
10411 auto *ExactFPMathInst = Requirements.getExactFPInst();
10412 return OptimizationRemarkAnalysisFPCommute(DEBUG_TYPE"loop-vectorize", "CantReorderFPOps",
10413 ExactFPMathInst->getDebugLoc(),
10414 ExactFPMathInst->getParent())
10415 << "loop not vectorized: cannot prove it is safe to reorder "
10416 "floating-point operations";
10417 });
10418 LLVM_DEBUG(dbgs() << "LV: loop not vectorized: cannot prove it is safe to "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: loop not vectorized: cannot prove it is safe to "
"reorder floating-point operations\n"; } } while (false)
10419 "reorder floating-point operations\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: loop not vectorized: cannot prove it is safe to "
"reorder floating-point operations\n"; } } while (false)
;
10420 Hints.emitRemarkWithHints();
10421 return false;
10422 }
10423
10424 bool UseInterleaved = TTI->enableInterleavedAccessVectorization();
10425 InterleavedAccessInfo IAI(PSE, L, DT, LI, LVL.getLAI());
10426
10427 // If an override option has been passed in for interleaved accesses, use it.
10428 if (EnableInterleavedMemAccesses.getNumOccurrences() > 0)
10429 UseInterleaved = EnableInterleavedMemAccesses;
10430
10431 // Analyze interleaved memory accesses.
10432 if (UseInterleaved) {
10433 IAI.analyzeInterleaving(useMaskedInterleavedAccesses(*TTI));
10434 }
10435
10436 // Use the cost model.
10437 LoopVectorizationCostModel CM(SEL, L, PSE, LI, &LVL, *TTI, TLI, DB, AC, ORE,
10438 F, &Hints, IAI);
10439 CM.collectValuesToIgnore();
10440 CM.collectElementTypesForWidening();
10441
10442 // Use the planner for vectorization.
10443 LoopVectorizationPlanner LVP(L, LI, TLI, TTI, &LVL, CM, IAI, PSE, Hints,
10444 Requirements, ORE);
10445
10446 // Get user vectorization factor and interleave count.
10447 ElementCount UserVF = Hints.getWidth();
10448 unsigned UserIC = Hints.getInterleave();
10449
10450 // Plan how to best vectorize, return the best VF and its cost.
10451 Optional<VectorizationFactor> MaybeVF = LVP.plan(UserVF, UserIC);
10452
10453 VectorizationFactor VF = VectorizationFactor::Disabled();
10454 unsigned IC = 1;
10455
10456 if (MaybeVF) {
10457 VF = *MaybeVF;
10458 // Select the interleave count.
10459 IC = CM.selectInterleaveCount(VF.Width, *VF.Cost.getValue());
10460 }
10461
10462 // Identify the diagnostic messages that should be produced.
10463 std::pair<StringRef, std::string> VecDiagMsg, IntDiagMsg;
10464 bool VectorizeLoop = true, InterleaveLoop = true;
10465 if (VF.Width.isScalar()) {
10466 LLVM_DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Vectorization is possible but not beneficial.\n"
; } } while (false)
;
10467 VecDiagMsg = std::make_pair(
10468 "VectorizationNotBeneficial",
10469 "the cost-model indicates that vectorization is not beneficial");
10470 VectorizeLoop = false;
10471 }
10472
10473 if (!MaybeVF && UserIC > 1) {
10474 // Tell the user interleaving was avoided up-front, despite being explicitly
10475 // requested.
10476 LLVM_DEBUG(dbgs() << "LV: Ignoring UserIC, because vectorization and "do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Ignoring UserIC, because vectorization and "
"interleaving should be avoided up front\n"; } } while (false
)
10477 "interleaving should be avoided up front\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Ignoring UserIC, because vectorization and "
"interleaving should be avoided up front\n"; } } while (false
)
;
10478 IntDiagMsg = std::make_pair(
10479 "InterleavingAvoided",
10480 "Ignoring UserIC, because interleaving was avoided up front");
10481 InterleaveLoop = false;
10482 } else if (IC == 1 && UserIC <= 1) {
10483 // Tell the user interleaving is not beneficial.
10484 LLVM_DEBUG(dbgs() << "LV: Interleaving is not beneficial.\n")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving is not beneficial.\n"
; } } while (false)
;
10485 IntDiagMsg = std::make_pair(
10486 "InterleavingNotBeneficial",
10487 "the cost-model indicates that interleaving is not beneficial");
10488 InterleaveLoop = false;
10489 if (UserIC == 1) {
10490 IntDiagMsg.first = "InterleavingNotBeneficialAndDisabled";
10491 IntDiagMsg.second +=
10492 " and is explicitly disabled or interleave count is set to 1";
10493 }
10494 } else if (IC > 1 && UserIC == 1) {
10495 // Tell the user interleaving is beneficial, but it explicitly disabled.
10496 LLVM_DEBUG(do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving is beneficial but is explicitly disabled."
; } } while (false)
10497 dbgs() << "LV: Interleaving is beneficial but is explicitly disabled.")do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleaving is beneficial but is explicitly disabled."
; } } while (false)
;
10498 IntDiagMsg = std::make_pair(
10499 "InterleavingBeneficialButDisabled",
10500 "the cost-model indicates that interleaving is beneficial "
10501 "but is explicitly disabled or interleave count is set to 1");
10502 InterleaveLoop = false;
10503 }
10504
10505 // Override IC if user provided an interleave count.
10506 IC = UserIC > 0 ? UserIC : IC;
10507
10508 // Emit diagnostic messages, if any.
10509 const char *VAPassName = Hints.vectorizeAnalysisPassName();
10510 if (!VectorizeLoop && !InterleaveLoop) {
10511 // Do not vectorize or interleaving the loop.
10512 ORE->emit([&]() {
10513 return OptimizationRemarkMissed(VAPassName, VecDiagMsg.first,
10514 L->getStartLoc(), L->getHeader())
10515 << VecDiagMsg.second;
10516 });
10517 ORE->emit([&]() {
10518 return OptimizationRemarkMissed(LV_NAME"loop-vectorize", IntDiagMsg.first,
10519 L->getStartLoc(), L->getHeader())
10520 << IntDiagMsg.second;
10521 });
10522 return false;
10523 } else if (!VectorizeLoop && InterleaveLoop) {
10524 LLVM_DEBUG(dbgs() << "LV: Interleave Count is " << IC << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleave Count is "
<< IC << '\n'; } } while (false)
;
10525 ORE->emit([&]() {
10526 return OptimizationRemarkAnalysis(VAPassName, VecDiagMsg.first,
10527 L->getStartLoc(), L->getHeader())
10528 << VecDiagMsg.second;
10529 });
10530 } else if (VectorizeLoop && !InterleaveLoop) {
10531 LLVM_DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Widthdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found a vectorizable loop ("
<< VF.Width << ") in " << DebugLocStr <<
'\n'; } } while (false)
10532 << ") in " << DebugLocStr << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found a vectorizable loop ("
<< VF.Width << ") in " << DebugLocStr <<
'\n'; } } while (false)
;
10533 ORE->emit([&]() {
10534 return OptimizationRemarkAnalysis(LV_NAME"loop-vectorize", IntDiagMsg.first,
10535 L->getStartLoc(), L->getHeader())
10536 << IntDiagMsg.second;
10537 });
10538 } else if (VectorizeLoop && InterleaveLoop) {
10539 LLVM_DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Widthdo { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found a vectorizable loop ("
<< VF.Width << ") in " << DebugLocStr <<
'\n'; } } while (false)
10540 << ") in " << DebugLocStr << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Found a vectorizable loop ("
<< VF.Width << ") in " << DebugLocStr <<
'\n'; } } while (false)
;
10541 LLVM_DEBUG(dbgs() << "LV: Interleave Count is " << IC << '\n')do { if (::llvm::DebugFlag && ::llvm::isCurrentDebugType
("loop-vectorize")) { dbgs() << "LV: Interleave Count is "
<< IC << '\n'; } } while (false)
;
10542 }
10543
10544 bool DisableRuntimeUnroll = false;
10545 MDNode *OrigLoopID = L->getLoopID();
10546 {
10547 // Optimistically generate runtime checks. Drop them if they turn out to not
10548 // be profitable. Limit the scope of Checks, so the cleanup happens
10549 // immediately after vector codegeneration is done.
10550 GeneratedRTChecks Checks(*PSE.getSE(), DT, LI,
10551 F->getParent()->getDataLayout());
10552 if (!VF.Width.isScalar() || IC > 1)
10553 Checks.Create(L, *LVL.getLAI(), PSE.getPredicate());
10554
10555 using namespace ore;
10556 if (!VectorizeLoop) {
10557 assert(IC > 1 && "interleave count should not be 1 or 0")(static_cast <bool> (IC > 1 && "interleave count should not be 1 or 0"
) ? void (0) : __assert_fail ("IC > 1 && \"interleave count should not be 1 or 0\""
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10557, __extension__
__PRETTY_FUNCTION__))
;
10558 // If we decided that it is not legal to vectorize the loop, then
10559 // interleave it.
10560 InnerLoopUnroller Unroller(L, PSE, LI, DT, TLI, TTI, AC, ORE, IC, &LVL,
10561 &CM, BFI, PSI, Checks);
10562
10563 VPlan &BestPlan = LVP.getBestPlanFor(VF.Width);
10564 LVP.executePlan(VF.Width, IC, BestPlan, Unroller, DT);
10565
10566 ORE->emit([&]() {
10567 return OptimizationRemark(LV_NAME"loop-vectorize", "Interleaved", L->getStartLoc(),
10568 L->getHeader())
10569 << "interleaved loop (interleaved count: "
10570 << NV("InterleaveCount", IC) << ")";
10571 });
10572 } else {
10573 // If we decided that it is *legal* to vectorize the loop, then do it.
10574
10575 // Consider vectorizing the epilogue too if it's profitable.
10576 VectorizationFactor EpilogueVF =
10577 CM.selectEpilogueVectorizationFactor(VF.Width, LVP);
10578 if (EpilogueVF.Width.isVector()) {
10579
10580 // The first pass vectorizes the main loop and creates a scalar epilogue
10581 // to be vectorized by executing the plan (potentially with a different
10582 // factor) again shortly afterwards.
10583 EpilogueLoopVectorizationInfo EPI(VF.Width, IC, EpilogueVF.Width, 1);
10584 EpilogueVectorizerMainLoop MainILV(L, PSE, LI, DT, TLI, TTI, AC, ORE,
10585 EPI, &LVL, &CM, BFI, PSI, Checks);
10586
10587 VPlan &BestMainPlan = LVP.getBestPlanFor(EPI.MainLoopVF);
10588 LVP.executePlan(EPI.MainLoopVF, EPI.MainLoopUF, BestMainPlan, MainILV,
10589 DT);
10590 ++LoopsVectorized;
10591
10592 simplifyLoop(L, DT, LI, SE, AC, nullptr, false /* PreserveLCSSA */);
10593 formLCSSARecursively(*L, *DT, LI, SE);
10594
10595 // Second pass vectorizes the epilogue and adjusts the control flow
10596 // edges from the first pass.
10597 EPI.MainLoopVF = EPI.EpilogueVF;
10598 EPI.MainLoopUF = EPI.EpilogueUF;
10599 EpilogueVectorizerEpilogueLoop EpilogILV(L, PSE, LI, DT, TLI, TTI, AC,
10600 ORE, EPI, &LVL, &CM, BFI, PSI,
10601 Checks);
10602
10603 VPlan &BestEpiPlan = LVP.getBestPlanFor(EPI.EpilogueVF);
10604
10605 // Ensure that the start values for any VPReductionPHIRecipes are
10606 // updated before vectorising the epilogue loop.
10607 VPBasicBlock *Header = BestEpiPlan.getEntry()->getEntryBasicBlock();
10608 for (VPRecipeBase &R : Header->phis()) {
10609 if (auto *ReductionPhi = dyn_cast<VPReductionPHIRecipe>(&R)) {
10610 if (auto *Resume = MainILV.getReductionResumeValue(
10611 ReductionPhi->getRecurrenceDescriptor())) {
10612 VPValue *StartVal = new VPValue(Resume);
10613 BestEpiPlan.addExternalDef(StartVal);
10614 ReductionPhi->setOperand(0, StartVal);
10615 }
10616 }
10617 }
10618
10619 LVP.executePlan(EPI.EpilogueVF, EPI.EpilogueUF, BestEpiPlan, EpilogILV,
10620 DT);
10621 ++LoopsEpilogueVectorized;
10622
10623 if (!MainILV.areSafetyChecksAdded())
10624 DisableRuntimeUnroll = true;
10625 } else {
10626 InnerLoopVectorizer LB(L, PSE, LI, DT, TLI, TTI, AC, ORE, VF.Width, IC,
10627 &LVL, &CM, BFI, PSI, Checks);
10628
10629 VPlan &BestPlan = LVP.getBestPlanFor(VF.Width);
10630 LVP.executePlan(VF.Width, IC, BestPlan, LB, DT);
10631 ++LoopsVectorized;
10632
10633 // Add metadata to disable runtime unrolling a scalar loop when there
10634 // are no runtime checks about strides and memory. A scalar loop that is
10635 // rarely used is not worth unrolling.
10636 if (!LB.areSafetyChecksAdded())
10637 DisableRuntimeUnroll = true;
10638 }
10639 // Report the vectorization decision.
10640 ORE->emit([&]() {
10641 return OptimizationRemark(LV_NAME"loop-vectorize", "Vectorized", L->getStartLoc(),
10642 L->getHeader())
10643 << "vectorized loop (vectorization width: "
10644 << NV("VectorizationFactor", VF.Width)
10645 << ", interleaved count: " << NV("InterleaveCount", IC) << ")";
10646 });
10647 }
10648
10649 if (ORE->allowExtraAnalysis(LV_NAME"loop-vectorize"))
10650 checkMixedPrecision(L, ORE);
10651 }
10652
10653 Optional<MDNode *> RemainderLoopID =
10654 makeFollowupLoopID(OrigLoopID, {LLVMLoopVectorizeFollowupAll,
10655 LLVMLoopVectorizeFollowupEpilogue});
10656 if (RemainderLoopID.hasValue()) {
10657 L->setLoopID(RemainderLoopID.getValue());
10658 } else {
10659 if (DisableRuntimeUnroll)
10660 AddRuntimeUnrollDisableMetaData(L);
10661
10662 // Mark the loop as already vectorized to avoid vectorizing again.
10663 Hints.setAlreadyVectorized();
10664 }
10665
10666 assert(!verifyFunction(*L->getHeader()->getParent(), &dbgs()))(static_cast <bool> (!verifyFunction(*L->getHeader()
->getParent(), &dbgs())) ? void (0) : __assert_fail ("!verifyFunction(*L->getHeader()->getParent(), &dbgs())"
, "llvm/lib/Transforms/Vectorize/LoopVectorize.cpp", 10666, __extension__
__PRETTY_FUNCTION__))
;
10667 return true;
10668}
10669
10670LoopVectorizeResult LoopVectorizePass::runImpl(
10671 Function &F, ScalarEvolution &SE_, LoopInfo &LI_, TargetTransformInfo &TTI_,
10672 DominatorTree &DT_, BlockFrequencyInfo &BFI_, TargetLibraryInfo *TLI_,
10673 DemandedBits &DB_, AAResults &AA_, AssumptionCache &AC_,
10674 std::function<const LoopAccessInfo &(Loop &)> &GetLAA_,
10675 OptimizationRemarkEmitter &ORE_, ProfileSummaryInfo *PSI_) {
10676 SE = &SE_;
10677 LI = &LI_;
10678 TTI = &TTI_;
10679 DT = &DT_;
10680 BFI = &BFI_;
10681 TLI = TLI_;
10682 AA = &AA_;
10683 AC = &AC_;
10684 GetLAA = &GetLAA_;
10685 DB = &DB_;
10686 ORE = &ORE_;
10687 PSI = PSI_;
10688
10689 // Don't attempt if
10690 // 1. the target claims to have no vector registers, and
10691 // 2. interleaving won't help ILP.
10692 //
10693 // The second condition is necessary because, even if the target has no
10694 // vector registers, loop vectorization may still enable scalar
10695 // interleaving.
10696 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true)) &&
10697 TTI->getMaxInterleaveFactor(1) < 2)
10698 return LoopVectorizeResult(false, false);
10699
10700 bool Changed = false, CFGChanged = false;
10701
10702 // The vectorizer requires loops to be in simplified form.
10703 // Since simplification may add new inner loops, it has to run before the
10704 // legality and profitability checks. This means running the loop vectorizer
10705 // will simplify all loops, regardless of whether anything end up being
10706 // vectorized.
10707 for (auto &L : *LI)
10708 Changed |= CFGChanged |=
10709 simplifyLoop(L, DT, LI, SE, AC, nullptr, false /* PreserveLCSSA */);
10710
10711 // Build up a worklist of inner-loops to vectorize. This is necessary as
10712 // the act of vectorizing or partially unrolling a loop creates new loops
10713 // and can invalidate iterators across the loops.
10714 SmallVector<Loop *, 8> Worklist;
10715
10716 for (Loop *L : *LI)
10717 collectSupportedLoops(*L, LI, ORE, Worklist);
10718
10719 LoopsAnalyzed += Worklist.size();
10720
10721 // Now walk the identified inner loops.
10722 while (!Worklist.empty()) {
10723 Loop *L = Worklist.pop_back_val();
10724
10725 // For the inner loops we actually process, form LCSSA to simplify the
10726 // transform.
10727 Changed |= formLCSSARecursively(*L, *DT, LI, SE);
10728
10729 Changed |= CFGChanged |= processLoop(L);
10730 }
10731
10732 // Process each loop nest in the function.
10733 return LoopVectorizeResult(Changed, CFGChanged);
10734}
10735
10736PreservedAnalyses LoopVectorizePass::run(Function &F,
10737 FunctionAnalysisManager &AM) {
10738 auto &SE = AM.getResult<ScalarEvolutionAnalysis>(F);
10739 auto &LI = AM.getResult<LoopAnalysis>(F);
10740 auto &TTI = AM.getResult<TargetIRAnalysis>(F);
10741 auto &DT = AM.getResult<DominatorTreeAnalysis>(F);
10742 auto &BFI = AM.getResult<BlockFrequencyAnalysis>(F);
10743 auto &TLI = AM.getResult<TargetLibraryAnalysis>(F);
10744 auto &AA = AM.getResult<AAManager>(F);
10745 auto &AC = AM.getResult<AssumptionAnalysis>(F);
10746 auto &DB = AM.getResult<DemandedBitsAnalysis>(F);
10747 auto &ORE = AM.getResult<OptimizationRemarkEmitterAnalysis>(F);
10748
10749 auto &LAM = AM.getResult<LoopAnalysisManagerFunctionProxy>(F).getManager();
10750 std::function<const LoopAccessInfo &(Loop &)> GetLAA =
10751 [&](Loop &L) -> const LoopAccessInfo & {
10752 LoopStandardAnalysisResults AR = {AA, AC, DT, LI, SE,
10753 TLI, TTI, nullptr, nullptr, nullptr};
10754 return LAM.getResult<LoopAccessAnalysis>(L, AR);
10755 };
10756 auto &MAMProxy = AM.getResult<ModuleAnalysisManagerFunctionProxy>(F);
10757 ProfileSummaryInfo *PSI =
10758 MAMProxy.getCachedResult<ProfileSummaryAnalysis>(*F.getParent());
10759 LoopVectorizeResult Result =
10760 runImpl(F, SE, LI, TTI, DT, BFI, &TLI, DB, AA, AC, GetLAA, ORE, PSI);
10761 if (!Result.MadeAnyChange)
10762 return PreservedAnalyses::all();
10763 PreservedAnalyses PA;
10764
10765 // We currently do not preserve loopinfo/dominator analyses with outer loop
10766 // vectorization. Until this is addressed, mark these analyses as preserved
10767 // only for non-VPlan-native path.
10768 // TODO: Preserve Loop and Dominator analyses for VPlan-native path.
10769 if (!EnableVPlanNativePath) {
10770 PA.preserve<LoopAnalysis>();
10771 PA.preserve<DominatorTreeAnalysis>();
10772 }
10773
10774 if (Result.MadeCFGChange) {
10775 // Making CFG changes likely means a loop got vectorized. Indicate that
10776 // extra simplification passes should be run.
10777 // TODO: MadeCFGChanges is not a prefect proxy. Extra passes should only
10778 // be run if runtime checks have been added.
10779 AM.getResult<ShouldRunExtraVectorPasses>(F);
10780 PA.preserve<ShouldRunExtraVectorPasses>();
10781 } else {
10782 PA.preserveSet<CFGAnalyses>();
10783 }
10784 return PA;
10785}
10786
10787void LoopVectorizePass::printPipeline(
10788 raw_ostream &OS, function_ref<StringRef(StringRef)> MapClassName2PassName) {
10789 static_cast<PassInfoMixin<LoopVectorizePass> *>(this)->printPipeline(
10790 OS, MapClassName2PassName);
10791
10792 OS << "<";
10793 OS << (InterleaveOnlyWhenForced ? "" : "no-") << "interleave-forced-only;";
10794 OS << (VectorizeOnlyWhenForced ? "" : "no-") << "vectorize-forced-only;";
10795 OS << ">";
10796}