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
