High-Performance Data Science with RAPIDS

Zahra Ronaghi, NVIDIA
Webinar
ALCF Developer Sessions:  High-Performance Data Science with RAPIDS

High-Performance Data Science with RAPIDS


RAPIDS is a collection of open-source libraries for accelerating data science pipelines on GPUs, and is designed with familiar APIs for data scientists working in Python. We will present an overview of this platform, core libraries including cuDF (GPU-accelerated dataframes) and cuML (GPU-accelerated machine learning), and Dask on GPUs for large-scale data analytics.

About the Speaker


Zahra Ronaghi is a system software manager on the AI Infrastructure team at NVIDIA. She is primarily focused on GPU-accelerated machine learning and integration of RAPIDS libraries with cloud service providers and ML platforms. Prior to joining NVIDIA, Zahra was a postdoctoral fellow at Lawrence Berkeley National Laboratory (NERSC), where she worked on performance optimization of a tomographic reconstruction code and deep neural networks for neutrino telescopes.

Your Visit

RAPIDS is a collection of open-source libraries for accelerating data science pipelines on GPUs, and is designed with familiar APIs for data scientists working in Python. We will present an overview of this platform, core libraries including cuDF (GPU-accelerated dataframes) and cuML (GPU-accelerated machine learning), and Dask on GPUs for large-scale data analytics.