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What does this implement/fix? Explain your changes.
The computational performance guide lists ATLAS as the top choice for optimized BLAS backends, but:
ATLAS does not allow runtime configuration of threads the way OpenBLAS and MKL do, which is quite important when it comes to metaestimators and similar where joblib tries to set inner threads.
ATLAS needs to be compiled from source to get optimal performance, whereas the linked blog post installs a pre-built version from the Debian main repository which will not be optimized for the hardware where it's used.
In 2026, performance of ATLAS is unlikely to be better than that of more user-friendly libraries like MKL, OpenBLAS and BLIS (at least when it comes to x86 hardware), which allow controlling threads at runtime.
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This PR is introducing linting issues. Here's a summary of the issues. Note that you can avoid having linting issues by enabling pre-commit hooks. Instructions to enable them can be found here.
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cython-lint detected issues. Please fix them locally and push the changes. Here you can see the detected issues. Note that the installed cython-lint version is cython-lint=0.20.0.
Details
/home/runner/work/scikit-learn/scikit-learn/sklearn/cluster/_dbscan_inner.pyx:31:25: Outer for loop variable 'i' overwritten by inner for-loop target
Generated for commit: d59a62f. Link to the linter CI: here
Linting error is in a file that's not being modified in this PR.
In 2026, performance of ATLAS is unlikely to be better than that of more user-friendly libraries like MKL, OpenBLAS and BLIS (at least when it comes to x86 hardware), which allow controlling threads at runtime.
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Reference Issues/PRs
What does this implement/fix? Explain your changes.
The computational performance guide lists ATLAS as the top choice for optimized BLAS backends, but:
First time contributor introduction
AI usage disclosure
I used AI assistance for:
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