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Evaluate using Profile-Guided Optimization (PGO) and Post Link Optimization (PLO) #257

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zamazan4ik opened this issue Nov 17, 2023 · 1 comment

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@zamazan4ik
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Hi!

Recently I did many Profile-Guided Optimization (PGO) benchmarks on multiple projects (including static analysis tools and compilers like CPython, Rustc, Clang, Clangd, Clang Tidy, and many others) - the results are available here. Trying to enable PGO to the Numbat tooling could be a good thing to try.

I can suggest the following things to do:

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

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

Some PGO documentation examples in various projects:

After PGO, I can suggest evaluating LLVM BOLT as an additional optimization step after PGO - Post Link Optimization (PLO). This optimization technique is already integrated into the Clang, CPython, and Rustc build scripts. But I suggest starting with PGO - it's a more stable optimization than PLO in the general case.

For the Rust projects, I recommend starting PGO integration with cargo-pgo.

@sharkdp
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sharkdp commented Nov 20, 2023

You seem to post this in many different repositories, so I have to assume that you are following some agenda here that is not necessarily aligned with the project goals.

We currently don't have a performance problem in Numbat. If we do, and run out of more basic things to do, we can look in to PGO — of course.

@sharkdp sharkdp closed this as completed Nov 20, 2023
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