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Evaluate using Profile-Guided Optimization (PGO) and LLVM BOLT #7354

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@zamazan4ik

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@zamazan4ik

Is your feature request related to a problem? Please describe.
Not a problem - just an idea of how to potentially improve the Cube's performance.

Describe the solution you'd like

Recently I checked Profile-Guided Optimization (PGO) improvements on multiple projects. The results are available here. According to the tests, PGO helps with achieving better performance in many software domains like databases, compilers, network applications, etc. I think trying to optimize Cube (its Rust part since Rust supports PGO) with PGO can be a good idea.

I can suggest the following action points:

  • Perform PGO benchmarks on Cube. And if it shows improvements - add a note about possible improvements in Cube's 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 Cube according to their own workloads.
  • Optimize pre-built Cube binaries (like Docker containers) (if it's possible to prepare a good enough workload for PGO training)

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.

Additional context
For the Rust projects, I recommend starting with cargo-pgo. More details about PGO support in Rust can be found in the official docs.

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

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