Evaluate using Profile-Guided Optimization (PGO) and LLVM BOLT

[zamazan4ik]

Hi!

Recently I checked Profile-Guided Optimization (PGO) improvements on multiple projects. The results are here. E.g. PGO results for LLVM-related tooling are here. According to the tests, PGO usually helps with the compiler and compiler-like workloads (like static analysis) - e.g. Clang gets +20% compilation speed with PGO. That's why I think trying to optimize the Rust-Code-Analysis tool with PGO can be a good idea.

I can suggest the following action points:

• Perform PGO benchmarks on Rust-Code-Analysis. And if it shows improvements - add a note about possible improvements in Rust-Code-Analysis's tool performance with PGO.
• Providing an easier way (e.g. a build option) to build scripts with PGO can be helpful for the end-users and maintainers since they will be able to optimize the Rust-Code-Analysis tool according to their own workloads.
• Optimize pre-built binaries

Testing Post-Link Optimization techniques (like LLVM BOLT) would be interesting too (Clang and Rustc already use BOLT as an addition to PGO) but I recommend starting from the usual PGO.

I recommend trying to use PGO with cargo-pgo for the Rust code.

Here are some examples of how PGO optimization is integrated in other projects:

• Rustc: a CI script for the multi-stage build
• GCC:
  • Official docs, section "Building with profile feedback" (even AutoFDO build is supported)
  • A part in a "wonderful" configure script
• Clang: Docs
• Python:
  • CPython: README
  • Pyston: README
• Go: Bash script
• V8: Bazel flag
• ChakraCore: Scripts
• Chromium: Script
• Firefox: Docs
  • Thunderbird has PGO support too
• PHP - Makefile command and old Centminmod scripts
• MySQL: CMake script
• YugabyteDB: GitHub commit
• FoundationDB: Script
• Zstd: Makefile
• Foot: Scripts
• Windows Terminal: GitHub PR
• Pydantic-core: GitHub PR
• file.d: GitHub PR
• OceanBase: CMake flag

[marco-c]

Sounds good to me!