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Hi!
Recently I did many Profile-Guided Optimization (PGO) benchmarks on multiple projects (including many databases like PostrgreSQL, MongoDB, Redis, and many others) - the results are available here, all databases results are located here. So that's why I think it's worth trying to apply PGO to Proton as well.
I can suggest the following things to do:
- Evaluate PGO's applicability and benchmark results to Proton.
- If PGO helps to achieve better performance - add a note to Proton's documentation about that. In this case, users and maintainers will be aware of another optimization opportunity for Proton.
- Provide PGO integration into the build scripts. It can help users and maintainers easily apply PGO for their own workloads.
Here are some PGO integration examples in the existing build scripts in other projects:
- Rustc: a CI script for the multi-stage build
- GCC:
- Clang: Docs
- Python:
- 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
Some PGO documentation examples:
- ClickHouse: https://clickhouse.com/docs/en/operations/optimizing-performance/profile-guided-optimization
- Databend: https://databend.rs/doc/contributing/pgo
- Vector: https://vector.dev/docs/administration/tuning/pgo/
- Nebula: https://docs.nebula-graph.io/3.5.0/8.service-tuning/enable_autofdo_for_nebulagraph/
- GCC: Official docs, section "Building with profile feedback" (even AutoFDO build is supported)
- Clang:
After PGO, I can suggest evaluating LLVM BOLT as an additional optimization step after PGO.
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