Katrina Riehl
Dr. Katrina Riehl is a Principal Technical Product Manager at NVIDIA supporting CUDA and Python educational initiatives. For over two decades, Katrina has worked extensively in the fields of scientific computing, machine learning, data science, and visualization. Most notably, she has helped lead data science initiatives at the University of Texas Austin Applied Research Laboratory, Anaconda, Apple, Expedia Group, Cloudflare, and Snowflake.
She is an active volunteer in the Python open-source scientific software community, serving as a NumFOCUS Board member 2018-2024 and President 2021-2024. She continues to serve the NumFOCUS community on the NumFOCUS Advisory Council.
Sessions
As general purpose GPU programming has risen in popularity, many Python programmers have expressed a need to use this technology in their libraries and applications. They soon realize that the GPU landscape is vast and sometimes difficult to traverse for Python users.
In this talk, I will demystify the CUDA-enabled Accelerated Python landscape, focusing on the advantages and disadvantages of popular libraries, the common performance issues encountered, and the best practices to getting the most out of your GPU. Topics include CuPy, numba, nvmath-python, cuDF, and cuML.
This talk is beginner-friendly, but even the most seasoned programmer will gain insight into the Python GPU computing landscape.
If you have interest in NumPy, SciPy, Signal Processing, Simulation, DataFrames, Linear Programming (LP), Vehicle Routing Problems (VRP), or Graph Analysis, we'd love to hear what performance you're seeing and how you're measuring.