Add documentation about profile-guided optimization.

src/SUMMARY.md

@@ -85,6 +85,7 @@
   - [Debugging LLVM](./codegen/debugging.md)
 - [Emitting Diagnostics](./diag.md)
   - [JSON diagnostic format](./diag/json-format.md)
+- [Profile-guided Optimization](./profile-guided-optimization.md)
 
 ---
 

src/profile-guided-optimization.md

@@ -0,0 +1,132 @@
+# Profile Guided Optimization
+
+`rustc` supports doing profile-guided optimization (PGO).
+This chapter describes what PGO is and how the support for it is
+implemented in `rustc`.
+
+## What Is Profiled-Guided Optimization?
+
+The basic concept of PGO is to collect data about the typical execution of
+a program (e.g. which branches it is likely to take) and then use this data
+to inform optimizations such as inlining, machine-code layout,
+register allocation, etc.
+
+There are different ways of collecting data about a program's execution.
+One is to run the program inside a profiler (such as `perf`) and another
+is to create an instrumented binary, that is, a binary that has data
+collection built into it, and run that.
+The latter usually provides more accurate data.
+
+## How is PGO implemented in `rustc`?
+
+`rustc` current PGO implementation relies entirely on LLVM.
+LLVM actually [supports multiple forms][clang-pgo] of PGO:
+
+[clang-pgo]: https://clang.llvm.org/docs/UsersManual.html#profile-guided-optimization
+
+- Sampling-based PGO where an external profiling tool like `perf` is used
+  to collect data about a program's execution.
+- GCOV-based profiling, where code coverage infrastructure is used to collect
+  profiling information.
+- Front-end based instrumentation, where the compiler front-end (e.g. Clang)
+  inserts instrumentation intrinsics into the LLVM IR it generates.
+- IR-level instrumentation, where LLVM inserts the instrumentation intrinsics
+  itself during optimization passes.
+
+`rustc` supports only the last approach, IR-level instrumentation, mainly
+because it is almost exclusively implemented in LLVM and needs little
+maintenance on the Rust side. Fortunately, it is also the most modern approach,
+yielding the best results.
+
+So, we are dealing with an instrumentation-based approach, i.e. profiling data
+is generated by a specially instrumented version of the program that's being
+optimized. Instrumentation-based PGO has two components: a compile-time
+component and run-time component, and one needs to understand the overall
+workflow to see how they interact.
+
+### Overall Workflow
+
+Generating a PGO-optimized program involves the following four steps:
+
+1. Compile the program with instrumentation enabled (e.g. `rustc -Cprofile-generate main.rs`)
+2. Run the instrumented program (e.g. `./main`) which generates a `default-<id>.profraw` file
+3. Convert the `.profraw` file into a `.profdata` file using LLVM's `llvm-profdata` tool.
+4. Compile the program again, this time making use of the profiling data
+   (e.g. `rustc -Cprofile-use=merged.profdata main.rs`)
+
+### Compile-Time Aspects
+
+Depending on which step in the above workflow we are in, two different things
+can happen at compile time:
+
+#### Create Binaries with Instrumentation
+
+As mentioned above, the profiling instrumentation is added by LLVM.
+`rustc` instructs LLVM to do so [by setting the appropriate][pgo-gen-passmanager]
+flags when creating LLVM `PassManager`s:
+
+```C
+	// `PMBR` is an `LLVMPassManagerBuilderRef`
+    unwrap(PMBR)->EnablePGOInstrGen = true;
+    // Instrumented binaries have a default output path for the `.profraw` file
+    // hard-coded into them:
+    unwrap(PMBR)->PGOInstrGen = PGOGenPath;
+```
+
+`rustc` also has to make sure that some of the symbols from LLVM's profiling
+runtime are not removed [by marking the with the right export level][pgo-gen-symbols].
+
+[pgo-gen-passmanager]: https://github.com/rust-lang/rust/blob/1.34.1/src/rustllvm/PassWrapper.cpp#L412-L416
+[pgo-gen-symbols]:https://github.com/rust-lang/rust/blob/1.34.1/src/librustc_codegen_ssa/back/symbol_export.rs#L212-L225
+
+
+#### Compile Binaries Where Optimizations Make Use Of Profiling Data
+
+In the final step of the workflow described above, the program is compiled
+again, with the compiler using the gathered profiling data in order to drive
+optimization decisions. `rustc` again leaves most of the work to LLVM here,
+basically [just telling][pgo-use-passmanager] the LLVM `PassManagerBuilder`
+where the profiling data can be found:
+
+```C
+	unwrap(PMBR)->PGOInstrUse = PGOUsePath;
+```
+
+[pgo-use-passmanager]: https://github.com/rust-lang/rust/blob/1.34.1/src/rustllvm/PassWrapper.cpp#L417-L420
+
+LLVM does the rest (e.g. setting branch weights, marking functions with
+`cold` or `inlinehint`, etc).
+
+
+### Runtime Aspects
+
+Instrumentation-based approaches always also have a runtime component, i.e.
+once we have an instrumented program, that program needs to be run in order
+to generate profiling data, and collecting and persisting this profiling
+data needs some infrastructure in place.
+
+In the case of LLVM, these runtime components are implemented in
+[compiler-rt][compiler-rt-profile] and statically linked into any instrumented
+binaries.
+The `rustc` version of this can be found in `src/libprofiler_builtins` which
+basically packs the C code from `compiler-rt` into a Rust crate.
+
+In order for `libprofiler_builtins` to be built, `profiler = true` must be set
+in `rustc`'s `config.toml`.
+
+[compiler-rt-profile]: https://github.com/llvm/llvm-project/tree/master/compiler-rt/lib/profile
+
+## Testing PGO
+
+Since the PGO workflow spans multiple compiler invocations most testing happens
+in [run-make tests][rmake-tests] (the relevant tests have `pgo` in their name).
+There is also a [codegen test][codegen-test] that checks that some expected
+instrumentation artifacts show up in LLVM IR.
+
+[rmake-tests]: https://github.com/rust-lang/rust/tree/master/src/test/run-make-fulldeps
+[codegen-test]: https://github.com/rust-lang/rust/blob/master/src/test/codegen/pgo-instrumentation.rs
+
+## Additional Information
+
+Clang's documentation contains a good overview on PGO in LLVM here:
+https://clang.llvm.org/docs/UsersManual.html#profile-guided-optimization