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Evaluate using Profile-Guided Optimization (PGO) and LLVM BOLT for Perspective C++ data engine #2405

@zamazan4ik

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@zamazan4ik

Hi!

Recently I checked Profile-Guided Optimization (PGO) improvements on many projects. All current results are available here. According to the multiple tests, PGO can help with improving performance in many cases (including databases). Since Perspective cares about the performance, I think trying to optimize Perspective's C++ part with PGO would be a good idea.

I can suggest the following action points:

  • Perform PGO benchmarks on Perspective. And if it shows improvements - add a note to the documentation about possible improvements in Perspective 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 Perspective according to their own workloads.
  • Optimize pre-built Perspective binaries with PGO.

Since the Perspective native part is the library, I think the Pydantic-core experience can be reused here. Also, Clang supports PGO for shared libraries.

Maybe 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.

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

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