NCSA staff who would like to submit an item for the calendar can email newsdesk@ncsa.illinois.edu.
This workshop will give you hands-on experience accelerating Python codes with NVIDIA GPUs. We will utilize code samples in two main categories to introduce you to Python GPU-accelerated computing. First, we will explore drop-in replacements for SciPy and NumPy codes through the CuPy library. Then we will cover NVIDIA RAPIDS, which provides GPU acceleration for end-to-end data science workloads. Finally, we will over Warp for differentiable simulation codes. By the end of the workshop, you will have the skills to start accelerating your Python codes with NVIDIA GPUs!
Prerequisites: Basic familiarity with Python. Familiarity with NumPy, and/or Scikit-learn is beneficial.
Instructor: Zoe Ryan is a solutions architect at NVIDIA, working with higher education institutions and researchers. She joined NVIDIA in 2020 after studying computer science and mathematics at Harvey Mudd College. She has worked in embedded systems/simulations and GPU-accelerated high-performance computing. Now, she is focused on helping researchers adopt and fully utilize GPU technology across domains.
Register by May 16, 2025
Zoom coordinates will be sent before the workshop