Evaluate OasysDB using Profile-Guided Optimization (PGO) and Post-Link Optimization (PLO)

[zamazan4ik]

Hi!

Recently I did many Profile-Guided Optimization (PGO) benchmarks on multiple projects (including many databases like PostgreSQL, ClickHouse, Redis, MongoDB, etc.) - the results are available here, database-related results could be checked here. That's why I think it's worth trying to apply PGO to OasysDB to improve the database performance.

I can suggest the following things to do:

• Evaluate PGO's results on OasysDB.
• If PGO helps to achieve better performance - add a note to OasysDB's documentation about that. In this case, users and maintainers will be aware of another optimization opportunity for OasysDB.
• Provide PGO integration into the build scripts. It can help users and maintainers easily apply PGO for their workloads.
• Optimize prebuilt OasysDB binaries (like Docker images) with PGO.

Here are some examples of how PGO is already integrated into other projects' build scripts:

• 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
• ISPC: CMake scipts
• NodeJS: Configure script
• Android Open Source Project (AOSP):
  • Official documentation
  • Committed PGO profiles: repository
• DMD: Custom build rule
• LDC: GitHub action
• tsv-utils: Makefile
• Erlang OTP: Makefile
• Clingo (PGO enabled only in Spack): Package recipe
• SWI-Prolog:
  • Script
  • CMake module
• hck: Justfile

Here are some examples how PGO-related documentation could look like in the project:

• 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:
  • https://llvm.org/docs/HowToBuildWithPGO.html
  • https://llvm.org/docs/AdvancedBuilds.html
• tsv-utils: https://github.com/eBay/tsv-utils/blob/master/docs/BuildingWithLTO.md

After PGO, I can suggest evaluating PLO with LLVM BOLT as an additional optimization step after PGO.

Below are listed some BOLT results:

• Rustc:
  • Rustc itself (GitHub PR)
  • LLVM in Rustc (Reddit)
• CPython: GitHub PR
• YDB: GitHub comment
• Clang:
  • Slides
  • Results on building Clang
  • Linaro results
  • on AMD 7950X3D
  • GitHub comment from LLVM
• LDC: GitHub comment
• HHVM, Proxygen and others: Facebook paper
• NodeJS: Blog
• Chromium: Blog
• MySQL, MongoDB, memcached, Verilator: Paper

Since the project is in its very early stages, I think right now it's not worth trying to integrate PGO into OasysDB. However, in the future, PGO could be a good thing to test with OssysDB.

[edwinkys]

Hi @zamazan4ik

Thank you for the suggestion. As you have mentioned, the project is currently in its very early stage and many things about the project is subjected to change. Once the project mature a little more, I will consider looking more about integrating PGO for OasysDB.