Debugging with XRay

This document shows an example of how you would go about analyzing applications built with XRay instrumentation. Here we will attempt to debug llc compiling some sample LLVM IR generated by Clang.

Building with XRay

To debug an application with XRay instrumentation, we need to build it with a Clang that supports the -fxray-instrument option. See XRay for more technical details of how XRay works for background information.

In our example, we need to add -fxray-instrument to the list of flags passed to Clang when building a binary. Note that we need to link with Clang as well to get the XRay runtime linked in appropriately. For building llc with XRay, we do something similar below for our LLVM build:

$ mkdir -p llvm-build && cd llvm-build
# Assume that the LLVM sources are at ../llvm
$ cmake -GNinja ../llvm -DCMAKE_BUILD_TYPE=Release \
    -DCMAKE_C_FLAGS_RELEASE="-fxray-instrument" -DCMAKE_CXX_FLAGS="-fxray-instrument" \
# Once this finishes, we should build llc
$ ninja llc

To verify that we have an XRay instrumented binary, we can use objdump to look for the xray_instr_map section.

$ objdump -h -j xray_instr_map ./bin/llc
./bin/llc:     file format elf64-x86-64

Sections:
Idx Name          Size      VMA               LMA               File off  Algn
 14 xray_instr_map 00002fc0  00000000041516c6  00000000041516c6  03d516c6  2**0
                  CONTENTS, ALLOC, LOAD, READONLY, DATA

Getting Traces

By default, XRay does not write out the trace files or patch the application before main starts. If we just run llc it should just work like a normally built binary. However, if we want to get a full trace of the application’s operations (of the functions we do end up instrumenting with XRay) then we need to enable XRay at application start. To do this, XRay checks the XRAY_OPTIONS environment variable.

# The following doesn't create an XRay trace by default.
$ ./bin/llc input.ll

# We need to set the XRAY_OPTIONS to enable some features.
$ XRAY_OPTIONS="patch_premain=true xray_mode=xray-basic" ./bin/llc input.ll
==69819==XRay: Log file in 'xray-log.llc.m35qPB'

At this point we now have an XRay trace we can start analysing.

The llvm-xray Tool

Having a trace then allows us to do basic accounting of the functions that were instrumented, and how much time we’re spending in parts of the code. To make sense of this data, we use the llvm-xray tool which has a few subcommands to help us understand our trace.

One of the simplest things we can do is to get an accounting of the functions that have been instrumented. We can see an example accounting with llvm-xray account:

$ llvm-xray account xray-log.llc.m35qPB -top=10 -sort=sum -sortorder=dsc -instr_map ./bin/llc
Functions with latencies: 29
   funcid      count [      min,       med,       90p,       99p,       max]       sum  function
      187        360 [ 0.000000,  0.000001,  0.000014,  0.000032,  0.000075]  0.001596  LLLexer.cpp:446:0: llvm::LLLexer::LexIdentifier()
       85        130 [ 0.000000,  0.000000,  0.000018,  0.000023,  0.000156]  0.000799  X86ISelDAGToDAG.cpp:1984:0: (anonymous namespace)::X86DAGToDAGISel::Select(llvm::SDNode*)
      138        130 [ 0.000000,  0.000000,  0.000017,  0.000155,  0.000155]  0.000774  SelectionDAGISel.cpp:2963:0: llvm::SelectionDAGISel::SelectCodeCommon(llvm::SDNode*, unsigned char const*, unsigned int)
      188        103 [ 0.000000,  0.000000,  0.000003,  0.000123,  0.000214]  0.000737  LLParser.cpp:2692:0: llvm::LLParser::ParseValID(llvm::ValID&, llvm::LLParser::PerFunctionState*)
       88          1 [ 0.000562,  0.000562,  0.000562,  0.000562,  0.000562]  0.000562  X86ISelLowering.cpp:83:0: llvm::X86TargetLowering::X86TargetLowering(llvm::X86TargetMachine const&, llvm::X86Subtarget const&)
      125        102 [ 0.000001,  0.000003,  0.000010,  0.000017,  0.000049]  0.000471  Verifier.cpp:3714:0: (anonymous namespace)::Verifier::visitInstruction(llvm::Instruction&)
       90          8 [ 0.000023,  0.000035,  0.000106,  0.000106,  0.000106]  0.000342  X86ISelLowering.cpp:3363:0: llvm::X86TargetLowering::LowerCall(llvm::TargetLowering::CallLoweringInfo&, llvm::SmallVectorImpl<llvm::SDValue>&) const
      124         32 [ 0.000003,  0.000007,  0.000016,  0.000041,  0.000041]  0.000310  Verifier.cpp:1967:0: (anonymous namespace)::Verifier::visitFunction(llvm::Function const&)
      123          1 [ 0.000302,  0.000302,  0.000302,  0.000302,  0.000302]  0.000302  LLVMContextImpl.cpp:54:0: llvm::LLVMContextImpl::~LLVMContextImpl()
      139         46 [ 0.000000,  0.000002,  0.000006,  0.000008,  0.000019]  0.000138  TargetLowering.cpp:506:0: llvm::TargetLowering::SimplifyDemandedBits(llvm::SDValue, llvm::APInt const&, llvm::APInt&, llvm::APInt&, llvm::TargetLowering::TargetLoweringOpt&, unsigned int, bool) const

This shows us that for our input file, llc spent the most cumulative time in the lexer (a total of 1 millisecond). If we wanted for example to work with this data in a spreadsheet, we can output the results as CSV using the -format=csv option to the command for further analysis.

If we want to get a textual representation of the raw trace we can use the llvm-xray convert tool to get YAML output. The first few lines of that output for an example trace would look like the following:

$ llvm-xray convert -f yaml -symbolize -instr_map=./bin/llc xray-log.llc.m35qPB
---
header:
  version:         1
  type:            0
  constant-tsc:    true
  nonstop-tsc:     true
  cycle-frequency: 2601000000
records:
  - { type: 0, func-id: 110, function: __cxx_global_var_init.8, cpu: 37, thread: 69819, kind: function-enter, tsc: 5434426023268520 }
  - { type: 0, func-id: 110, function: __cxx_global_var_init.8, cpu: 37, thread: 69819, kind: function-exit, tsc: 5434426023523052 }
  - { type: 0, func-id: 164, function: __cxx_global_var_init, cpu: 37, thread: 69819, kind: function-enter, tsc: 5434426029925386 }
  - { type: 0, func-id: 164, function: __cxx_global_var_init, cpu: 37, thread: 69819, kind: function-exit, tsc: 5434426030031128 }
  - { type: 0, func-id: 142, function: '(anonymous namespace)::CommandLineParser::ParseCommandLineOptions(int, char const* const*, llvm::StringRef, llvm::raw_ostream*)', cpu: 37, thread: 69819, kind: function-enter, tsc: 5434426046951388 }
  - { type: 0, func-id: 142, function: '(anonymous namespace)::CommandLineParser::ParseCommandLineOptions(int, char const* const*, llvm::StringRef, llvm::raw_ostream*)', cpu: 37, thread: 69819, kind: function-exit, tsc: 5434426047282020 }
  - { type: 0, func-id: 187, function: 'llvm::LLLexer::LexIdentifier()', cpu: 37, thread: 69819, kind: function-enter, tsc: 5434426047857332 }
  - { type: 0, func-id: 187, function: 'llvm::LLLexer::LexIdentifier()', cpu: 37, thread: 69819, kind: function-exit, tsc: 5434426047984152 }
  - { type: 0, func-id: 187, function: 'llvm::LLLexer::LexIdentifier()', cpu: 37, thread: 69819, kind: function-enter, tsc: 5434426048036584 }
  - { type: 0, func-id: 187, function: 'llvm::LLLexer::LexIdentifier()', cpu: 37, thread: 69819, kind: function-exit, tsc: 5434426048042292 }
  - { type: 0, func-id: 187, function: 'llvm::LLLexer::LexIdentifier()', cpu: 37, thread: 69819, kind: function-enter, tsc: 5434426048055056 }
  - { type: 0, func-id: 187, function: 'llvm::LLLexer::LexIdentifier()', cpu: 37, thread: 69819, kind: function-exit, tsc: 5434426048067316 }

Controlling Fidelity

So far in our examples, we haven’t been getting full coverage of the functions we have in the binary. To get that, we need to modify the compiler flags so that we can instrument more (if not all) the functions we have in the binary. We have two options for doing that, and we explore both of these below.

Instruction Threshold

The first “blunt” way of doing this is by setting the minimum threshold for function bodies to 1. We can do that with the -fxray-instruction-threshold=N flag when building our binary. We rebuild llc with this option and observe the results:

$ rm CMakeCache.txt
$ cmake -GNinja ../llvm -DCMAKE_BUILD_TYPE=Release \
    -DCMAKE_C_FLAGS_RELEASE="-fxray-instrument -fxray-instruction-threshold=1" \
    -DCMAKE_CXX_FLAGS="-fxray-instrument -fxray-instruction-threshold=1"
$ ninja llc
$ XRAY_OPTIONS="patch_premain=true" ./bin/llc input.ll
==69819==XRay: Log file in 'xray-log.llc.5rqxkU'

$ llvm-xray account xray-log.llc.5rqxkU -top=10 -sort=sum -sortorder=dsc -instr_map ./bin/llc
Functions with latencies: 36652
 funcid      count [      min,       med,       90p,       99p,       max]       sum  function
     75          1 [ 0.672368,  0.672368,  0.672368,  0.672368,  0.672368]  0.672368  llc.cpp:271:0: main
     78          1 [ 0.626455,  0.626455,  0.626455,  0.626455,  0.626455]  0.626455  llc.cpp:381:0: compileModule(char**, llvm::LLVMContext&)
 139617          1 [ 0.472618,  0.472618,  0.472618,  0.472618,  0.472618]  0.472618  LegacyPassManager.cpp:1723:0: llvm::legacy::PassManager::run(llvm::Module&)
 139610          1 [ 0.472618,  0.472618,  0.472618,  0.472618,  0.472618]  0.472618  LegacyPassManager.cpp:1681:0: llvm::legacy::PassManagerImpl::run(llvm::Module&)
 139612          1 [ 0.470948,  0.470948,  0.470948,  0.470948,  0.470948]  0.470948  LegacyPassManager.cpp:1564:0: (anonymous namespace)::MPPassManager::runOnModule(llvm::Module&)
 139607          2 [ 0.147345,  0.315994,  0.315994,  0.315994,  0.315994]  0.463340  LegacyPassManager.cpp:1530:0: llvm::FPPassManager::runOnModule(llvm::Module&)
 139605         21 [ 0.000002,  0.000002,  0.102593,  0.213336,  0.213336]  0.463331  LegacyPassManager.cpp:1491:0: llvm::FPPassManager::runOnFunction(llvm::Function&)
 139563      26096 [ 0.000002,  0.000002,  0.000037,  0.000063,  0.000215]  0.225708  LegacyPassManager.cpp:1083:0: llvm::PMDataManager::findAnalysisPass(void const*, bool)
 108055        188 [ 0.000002,  0.000120,  0.001375,  0.004523,  0.062624]  0.159279  MachineFunctionPass.cpp:38:0: llvm::MachineFunctionPass::runOnFunction(llvm::Function&)
  62635         22 [ 0.000041,  0.000046,  0.000050,  0.126744,  0.126744]  0.127715  X86TargetMachine.cpp:242:0: llvm::X86TargetMachine::getSubtargetImpl(llvm::Function const&) const

Instrumentation Attributes

The other way is to use configuration files for selecting which functions should always be instrumented by the compiler. This gives us a way of ensuring that certain functions are either always or never instrumented by not having to add the attribute to the source.

To use this feature, you can define one file for the functions to always instrument, and another for functions to never instrument. The format of these files are exactly the same as the SanitizerLists files that control similar things for the sanitizer implementations. For example, we can have two different files like below:

# always-instrument.txt
# always instrument functions that match the following filters:
fun:main

# never-instrument.txt
# never instrument functions that match the following filters:
fun:__cxx_*

Given the above two files we can re-build by providing those two files as arguments to clang as -fxray-always-instrument=always-instrument.txt or -fxray-never-instrument=never-instrument.txt.

The XRay stack tool

Given a trace, and optionally an instrumentation map, the llvm-xray stack command can be used to analyze a call stack graph constructed from the function call timeline.

The simplest way to use the command is simply to output the top stacks by call count and time spent.

$ llvm-xray stack xray-log.llc.5rqxkU -instr_map ./bin/llc

Unique Stacks: 3069
Top 10 Stacks by leaf sum:

Sum: 9633790
lvl   function                                                            count              sum
#0    main                                                                    1         58421550
#1    compileModule(char**, llvm::LLVMContext&)                               1         51440360
#2    llvm::legacy::PassManagerImpl::run(llvm::Module&)                       1         40535375
#3    llvm::FPPassManager::runOnModule(llvm::Module&)                         2         39337525
#4    llvm::FPPassManager::runOnFunction(llvm::Function&)                     6         39331465
#5    llvm::PMDataManager::verifyPreservedAnalysis(llvm::Pass*)             399         16628590
#6    llvm::PMTopLevelManager::findAnalysisPass(void const*)               4584         15155600
#7    llvm::PMDataManager::findAnalysisPass(void const*, bool)            32088          9633790

..etc..

In the default mode, identical stacks on different threads are independently aggregated. In a multithreaded program, you may end up having identical call stacks fill your list of top calls.

To address this, you may specify the -aggregate-threads or -per-thread-stacks flags. -per-thread-stacks treats the thread id as an implicit root in each call stack tree, while -aggregate-threads combines identical stacks from all threads.

Flame Graph Generation

The llvm-xray stack tool may also be used to generate flamegraphs for visualizing your instrumented invocations. The tool does not generate the graphs themselves, but instead generates a format that can be used with Brendan Gregg’s FlameGraph tool, currently available on github.

To generate output for a flamegraph, a few more options are necessary.

  • -all-stacks - Emits all of the stacks instead of just the top stacks.
  • -stack-format - Choose the flamegraph output format ‘flame’.
  • -aggregation-type - Choose the metric to graph.

You may pipe the command output directly to the flamegraph tool to obtain an svg file.

$llvm-xray stack xray-log.llc.5rqxkU -instr_map ./bin/llc -stack-format=flame -aggregation-type=time -all-stacks | \
/path/to/FlameGraph/flamegraph.pl > flamegraph.svg

If you open the svg in a browser, mouse events allow exploring the call stacks.

Further Exploration

The llvm-xray tool has a few other subcommands that are in various stages of being developed. One interesting subcommand that can highlight a few interesting things is the graph subcommand. Given for example the following toy program that we build with XRay instrumentation, we can see how the generated graph may be a helpful indicator of where time is being spent for the application.

// sample.cc
#include <iostream>
#include <thread>

[[clang::xray_always_instrument]] void f() {
  std::cerr << '.';
}

[[clang::xray_always_instrument]] void g() {
  for (int i = 0; i < 1 << 10; ++i) {
    std::cerr << '-';
  }
}

int main(int argc, char* argv[]) {
  std::thread t1([] {
    for (int i = 0; i < 1 << 10; ++i)
      f();
  });
  std::thread t2([] {
    g();
  });
  t1.join();
  t2.join();
  std::cerr << '\n';
}

We then build the above with XRay instrumentation:

$ clang++ -o sample -O3 sample.cc -std=c++11 -fxray-instrument -fxray-instruction-threshold=1
$ XRAY_OPTIONS="patch_premain=true" ./sample

We can then explore the graph rendering of the trace generated by this sample application. We assume you have the graphviz toosl available in your system, including both unflatten and dot. If you prefer rendering or exploring the graph using another tool, then that should be feasible as well. llvm-xray graph will create DOT format graphs which should be usable in most graph rendering applications. One example invocation of the llvm-xray graph command should yield some interesting insights to the workings of C++ applications:

$ llvm-xray graph xray-log.sample.* -m sample -color-edges=sum -edge-label=sum \
    | unflatten -f -l10 | dot -Tsvg -o sample.svg

Next Steps

If you have some interesting analyses you’d like to implement as part of the llvm-xray tool, please feel free to propose them on the llvm-dev@ mailing list. The following are some ideas to inspire you in getting involved and potentially making things better.

  • Implement a query/filtering library that allows for finding patterns in the XRay traces.
  • A conversion from the XRay trace onto something that can be visualised better by other tools (like the Chrome trace viewer for example).
  • Collecting function call stacks and how often they’re encountered in the XRay trace.