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Scipy>=1.15 was leading to significant slowdowns in CI due to issues with OpenBLAS configuration (see scipy/scipy#22438). Thanks to suggestions by SciPy maintainers, we've found a solution that resolves the slowdown without modifying and global configurations for OpenBLAS.

This PR wraps minimize calls in minimize_with_timeout in a with threadpool_limits(limits=1, user_api="blas") context, which makes OpenBLAS operate single-threaded within the context. Since PyTorch relies on OpenMP & MKL rather than OpenBLAS, this does not affect the evaluations of the acquisition functions or the MLL.

Test Plan:
Compare runtimes in the following tutorial workflows
Baseline - with scipy 1.14.1, without threadpool_limits: https://github.com/pytorch/botorch/actions/runs/13044166839/job/36391816602
With scipy 1.14.1, with threadpool_limits: https://github.com/pytorch/botorch/actions/runs/13044167834/job/36391818438
With scipy 1.15.1, with threadpool_limits: https://github.com/pytorch/botorch/actions/runs/13044245918/job/36392026548

@facebook-github-bot facebook-github-bot added the CLA Signed Do not delete this pull request or issue due to inactivity. label Jan 30, 2025
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@saitcakmak has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

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codecov bot commented Jan 30, 2025

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 99.98%. Comparing base (472de87) to head (8bf1230).
Report is 2 commits behind head on main.

Additional details and impacted files
@@           Coverage Diff           @@
##             main    #2712   +/-   ##
=======================================
  Coverage   99.98%   99.98%           
=======================================
  Files         202      202           
  Lines       18602    18604    +2     
=======================================
+ Hits        18600    18602    +2     
  Misses          2        2           

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Summary:
Scipy>=1.15 was leading to significant slowdowns in CI due to issues with OpenBLAS configuration (see scipy/scipy#22438). Thanks to suggestions by SciPy maintainers, we've found a solution that resolves the slowdown without modifying and global configurations for OpenBLAS. 

This PR wraps `minimize` calls in `minimize_with_timeout` in a `with threadpool_limits(limits=1, user_api="blas")` context, which makes OpenBLAS operate single-threaded within the context. Since PyTorch relies on OpenMP & MKL rather than OpenBLAS, this does not affect the evaluations of the acquisition functions or the MLL.


Test Plan:
Compare runtimes in the following tutorial workflows
Baseline - with scipy 1.14.1, without `threadpool_limits`: https://github.com/pytorch/botorch/actions/runs/13044166839/job/36391816602
With scipy 1.14.1, with `threadpool_limits`: https://github.com/pytorch/botorch/actions/runs/13044167834/job/36391818438
With scipy 1.15.1, with `threadpool_limits`: https://github.com/pytorch/botorch/actions/runs/13044245918/job/36392026548

Differential Revision: D68874700

Pulled By: saitcakmak
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This pull request was exported from Phabricator. Differential Revision: D68874700

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@saitcakmak merged this pull request in acae12d.

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