PR comparison: sklearn-dev@cakedev0:ridge/optim_cholesky vs sklearn-dev@scikit-learn:main

Hardware

CPU

Intel(R) Core(TM) Ultra X7 358H

X86_64, 16 physical cores, 16 logical CPUs

31 GB RAM

GPU(s)

  • level_zero:gpu:0: Intel(R) Arc(TM) B390 GPU (29 GB)

sklearn-dev@scikit-learn:main

Python 3.12.13

Packages

  • scikit-learn @ 1.8.0rc1-779-gae50210b66
  • numpy 2.5.0 (conda-forge)
  • scipy 1.18.0 (conda-forge)
  • pandas 2.3.3 (conda-forge)

Threadpools

  • libopenblas 0.3.33 (16 threads)
  • libgomp (16 threads)

OpenMP

  • GNU libgomp (OpenMP 4.5)
  • GOMP_SPINCOUNT: 1

Full environment

view pixi env JSON

sklearn-dev@cakedev0:ridge/optim_cholesky

Python 3.12.13

Packages

  • scikit-learn @ 2053577a2
  • numpy 2.5.0 (conda-forge)
  • scipy 1.18.0 (conda-forge)
  • pandas 2.3.3 (conda-forge)

Threadpools

  • libopenblas 0.3.33 (16 threads)
  • libgomp (16 threads)

OpenMP

  • GNU libgomp (OpenMP 4.5)
  • GOMP_SPINCOUNT: 1

Full environment

view pixi env JSON

Detailed results