Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Evaluate using Profile-Guided Optimization (PGO) and LLVM BOLT #414

Closed
zamazan4ik opened this issue Oct 25, 2023 · 0 comments
Closed

Evaluate using Profile-Guided Optimization (PGO) and LLVM BOLT #414

zamazan4ik opened this issue Oct 25, 2023 · 0 comments

Comments

@zamazan4ik
Copy link

Hi!

Recently I checked Profile-Guided Optimization (PGO) improvements on multiple projects. The results are here. E.g. PGO results for LLVM-related tooling are here. According to the tests, PGO usually helps with the compiler and compiler-like workloads (like static analysis) - e.g. Clang gets +20% compilation speed with PGO. That's why I think optimizing the Gravity lang tooling (like the compiler) with PGO can be a good idea.

I can suggest the following action points:

  • Perform PGO benchmarks on the Gravity tooling. If it shows improvements - add a note about possible improvements in Gravity'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 the Gravity tools according to their own workloads.
  • Optimize pre-built binaries with PGO

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:

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants