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Exascale: ALCF Aurora Early Adopter Series to Hold Oct. 26 Intro to Intel Extensions of Scikit-learn for ML Frameworks

On Wednesday, Oct. 26 from 11 am to noon CT, the Argonne Leadership Computing Facility’s Aurora Early Adopter series will hold an online event entitled Intro to Intel Extensions of Scikit-learn to Accelerate Machine Learning Frameworks.

The event will be led by Bob Chesebrough, Intel solutions architect. Registration is here.

Scikit-learn is a library for machine learning, providing tools for ML and statistical modeling via a consistent interface in Python, including classification, regression, clustering, and dimensionality reduction. In this session, Chesebrough, will showcase the Intel Extension for Scikit-learn and how, with only a few lines of code, to speed up on CPUs many Scikit-learn standard ML algorithms such as kmeans, dbscan, and pca. He’ll also address how changing a few lines of code can target these same kernels for use on GPUs.

Takeaways:

  • Where to get and how to install the Intel extension, part of the Intel oneAPI AI Analytics Toolkit
  • Example scikit-learn algorithm speed up over stock scikit-learn
  • Demonstration of the single line of code that enumerates all the Intel-optimized scikit-learn functions
  • How to apply the functional patch to turn on Intel Extensions for Scikit-learn
  • How to apply the dpctl command to offload data and computation to an Intel GPU
  • Describe upcoming hands-on workshops for deeper dives

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