Workshop: NVIDIA "Using GPUs with Python"

In this workshop, you'll get hands-on experience accelerating Python codes with NVIDIA GPUs. We will utilize code samples in three main categories to introduce you to Python GPU accelerated computing. First, we will explore drop-in replacements for SciPy and NumPy code through the CuPy library. Next, we’ll cover NVIDIA RAPIDS, which provides GPU acceleration for end-to-end data science workloads. Finally, we'll cover Numba, which gives you the flexibility to write custom accelerated code without leaving the Python language. We'll finish with an end-to-end example that incorporates all the tools introduced to tackle a geospatial problem. By the end of the workshop, you'll have the skills to start accelerating your own Python codes with NVIDIA GPUs!

Register to attend

Attendees need to sign up for an NVIDIA developer account ahead of the workshop.
https://developer.nvidia.com/

Highlights

· Exploration of drop-in replacements for SciPy and NumPy code through CuPy library

· Utilization of NVIDIA RAPIDS to provide GPU acceleration for end-to-end data science workloads

· Effective use of Numba to write custom accelerated code

· Tackling a geospatial problem with end-to-end examples incorporating all the tools introduced

This is a hybrid event, offered in person at the Ohio Supercomputer Center's offices at the Ohio Technology Consortium, 1224 Kinnear Rd., Columbus, OH 43212, and online. Connection details will be provided via email to registrants prior to the event.