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<h1 id="profile-guided-optimization"><a class="header" href="#profile-guided-optimization">Profile-guided optimization</a></h1>
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<ul>
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<li><a href="#what-is-profiled-guided-optimization">What is profiled-guided optimization?</a></li>
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<li><a href="#how-is-pgo-implemented-in-rustc">How is PGO implemented in <code>rustc</code>?</a>
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<ul>
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<li><a href="#overall-workflow">Overall workflow</a></li>
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<li><a href="#compile-time-aspects">Compile-time aspects</a>
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<ul>
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<li><a href="#create-binaries-with-instrumentation">Create binaries with instrumentation</a></li>
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<li><a href="#compile-binaries-where-optimizations-make-use-of-profiling-data">Compile binaries where optimizations make use of profiling data</a></li>
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</ul>
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</li>
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<li><a href="#runtime-aspects">Runtime aspects</a></li>
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</ul>
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</li>
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<li><a href="#testing-pgo">Testing PGO</a></li>
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<li><a href="#additional-information">Additional information</a></li>
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</ul>
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<p><code>rustc</code> supports doing profile-guided optimization (PGO).
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This chapter describes what PGO is and how the support for it is
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implemented in <code>rustc</code>.</p>
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<h2 id="what-is-profiled-guided-optimization"><a class="header" href="#what-is-profiled-guided-optimization">What is profiled-guided optimization?</a></h2>
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<p>The basic concept of PGO is to collect data about the typical execution of
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a program (e.g. which branches it is likely to take) and then use this data
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to inform optimizations such as inlining, machine-code layout,
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register allocation, etc.</p>
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<p>There are different ways of collecting data about a program's execution.
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One is to run the program inside a profiler (such as <code>perf</code>) and another
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is to create an instrumented binary, that is, a binary that has data
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collection built into it, and run that.
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The latter usually provides more accurate data.</p>
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<h2 id="how-is-pgo-implemented-in-rustc"><a class="header" href="#how-is-pgo-implemented-in-rustc">How is PGO implemented in <code>rustc</code>?</a></h2>
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<p><code>rustc</code> current PGO implementation relies entirely on LLVM.
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LLVM actually <a href="https://clang.llvm.org/docs/UsersManual.html#profile-guided-optimization">supports multiple forms</a> of PGO:</p>
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<ul>
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<li>Sampling-based PGO where an external profiling tool like <code>perf</code> is used
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to collect data about a program's execution.</li>
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<li>GCOV-based profiling, where code coverage infrastructure is used to collect
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profiling information.</li>
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<li>Front-end based instrumentation, where the compiler front-end (e.g. Clang)
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inserts instrumentation intrinsics into the LLVM IR it generates (but see the
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<sup class="footnote-reference" id="fr-note-instrument-coverage-1"><a href="#footnote-note-instrument-coverage">1</a></sup>"Note").</li>
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<li>IR-level instrumentation, where LLVM inserts the instrumentation intrinsics
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itself during optimization passes.</li>
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</ul>
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<p><code>rustc</code> supports only the last approach, IR-level instrumentation, mainly
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because it is almost exclusively implemented in LLVM and needs little
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maintenance on the Rust side. Fortunately, it is also the most modern approach,
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yielding the best results.</p>
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<p>So, we are dealing with an instrumentation-based approach, i.e. profiling data
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is generated by a specially instrumented version of the program that's being
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optimized. Instrumentation-based PGO has two components: a compile-time
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component and run-time component, and one needs to understand the overall
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workflow to see how they interact.</p>
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<h3 id="overall-workflow"><a class="header" href="#overall-workflow">Overall workflow</a></h3>
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<p>Generating a PGO-optimized program involves the following four steps:</p>
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<ol>
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<li>Compile the program with instrumentation enabled (e.g. <code>rustc -C profile-generate main.rs</code>)</li>
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<li>Run the instrumented program (e.g. <code>./main</code>) which generates a <code>default-<id>.profraw</code> file</li>
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<li>Convert the <code>.profraw</code> file into a <code>.profdata</code> file using LLVM's <code>llvm-profdata</code> tool.</li>
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<li>Compile the program again, this time making use of the profiling data
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(e.g. <code>rustc -C profile-use=merged.profdata main.rs</code>)</li>
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</ol>
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<h3 id="compile-time-aspects"><a class="header" href="#compile-time-aspects">Compile-time aspects</a></h3>
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<p>Depending on which step in the above workflow we are in, two different things
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can happen at compile time:</p>
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<h4 id="create-binaries-with-instrumentation"><a class="header" href="#create-binaries-with-instrumentation">Create binaries with instrumentation</a></h4>
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<p>As mentioned above, the profiling instrumentation is added by LLVM.
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<code>rustc</code> instructs LLVM to do so <a href="https://github.com/rust-lang/rust/blob/1.34.1/src/rustllvm/PassWrapper.cpp#L412-L416">by setting the appropriate</a>
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flags when creating LLVM <code>PassManager</code>s:</p>
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<pre><code class="language-C"> // `PMBR` is an `LLVMPassManagerBuilderRef`
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unwrap(PMBR)->EnablePGOInstrGen = true;
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// Instrumented binaries have a default output path for the `.profraw` file
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// hard-coded into them:
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unwrap(PMBR)->PGOInstrGen = PGOGenPath;
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</code></pre>
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<p><code>rustc</code> also has to make sure that some of the symbols from LLVM's profiling
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runtime are not removed <a href="https://github.com/rust-lang/rust/blob/1.34.1/src/librustc_codegen_ssa/back/symbol_export.rs#L212-L225">by marking the with the right export level</a>.</p>
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<h4 id="compile-binaries-where-optimizations-make-use-of-profiling-data"><a class="header" href="#compile-binaries-where-optimizations-make-use-of-profiling-data">Compile binaries where optimizations make use of profiling data</a></h4>
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<p>In the final step of the workflow described above, the program is compiled
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again, with the compiler using the gathered profiling data in order to drive
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optimization decisions. <code>rustc</code> again leaves most of the work to LLVM here,
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basically <a href="https://github.com/rust-lang/rust/blob/1.34.1/src/rustllvm/PassWrapper.cpp#L417-L420">just telling</a> the LLVM <code>PassManagerBuilder</code>
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where the profiling data can be found:</p>
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<pre><code class="language-C"> unwrap(PMBR)->PGOInstrUse = PGOUsePath;
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</code></pre>
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<p>LLVM does the rest (e.g. setting branch weights, marking functions with
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<code>cold</code> or <code>inlinehint</code>, etc).</p>
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<h3 id="runtime-aspects"><a class="header" href="#runtime-aspects">Runtime aspects</a></h3>
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<p>Instrumentation-based approaches always also have a runtime component, i.e.
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once we have an instrumented program, that program needs to be run in order
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to generate profiling data, and collecting and persisting this profiling
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data needs some infrastructure in place.</p>
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<p>In the case of LLVM, these runtime components are implemented in
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<a href="https://github.com/llvm/llvm-project/tree/main/compiler-rt/lib/profile">compiler-rt</a> and statically linked into any instrumented
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binaries.
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The <code>rustc</code> version of this can be found in <code>library/profiler_builtins</code> which
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basically packs the C code from <code>compiler-rt</code> into a Rust crate.</p>
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<p>In order for <code>profiler_builtins</code> to be built, <code>profiler = true</code> must be set
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in <code>rustc</code>'s <code>bootstrap.toml</code>.</p>
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<h2 id="testing-pgo"><a class="header" href="#testing-pgo">Testing PGO</a></h2>
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<p>Since the PGO workflow spans multiple compiler invocations most testing happens
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in <a href="https://github.com/rust-lang/rust/tree/master/tests/run-make">run-make tests</a> (the relevant tests have <code>pgo</code> in their name).
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There is also a <a href="https://github.com/rust-lang/rust/blob/master/tests/codegen/pgo-instrumentation.rs">codegen test</a> that checks that some expected
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instrumentation artifacts show up in LLVM IR.</p>
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<h2 id="additional-information"><a class="header" href="#additional-information">Additional information</a></h2>
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<p>Clang's documentation contains a good overview on <a href="https://clang.llvm.org/docs/UsersManual.html#profile-guided-optimization">PGO in LLVM</a>.</p>
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<hr>
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<ol class="footnote-definition"><li id="footnote-note-instrument-coverage">
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<p>Note: <code>rustc</code> now supports front-end-based coverage
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instrumentation, via the experimental option
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<a href="./llvm-coverage-instrumentation.html"><code>-C instrument-coverage</code></a>, but using these
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coverage results for PGO has not been attempted at this time. <a href="#fr-note-instrument-coverage-1">↩</a></p>
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</li>
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</ol>
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