Using CuPyNumeric and the Legate Ecosystem for Multi-GPU Scaling on Marlowe

Using CuPyNumeric and the Legate Ecosystem for Multi-GPU Scaling on Marlowe

Abstract: Discover how to use CuPyNumeric for seamless scaling numPy code to multi-GPU and multi-node setups. This workshop will discuss the best practices and uses of cuPyNumeric with real world examples and performance comparisons.

Speaker: Marcus Manos is a Solutions Architect at NVIDIA working with Financial Services customers. He received his masters in Data Science  from the University of California, Berkeley; where he trained deep learning models. While at Nvidia, Marcus has worked on a diverse set of problems involving LLM inference, reasoning model training, cuPyNumeric.

Speaker: Manolis Papadakis is a Software Engineering Manager at NVIDIA. Manolis joined NVIDIA after completing his Ph.D. in computer science at Stanford University, with a focus on distributed and scientific computing. He has since been working on making Legate/cuPyNumeric a reality.

About the NVIDIA GPU Computing Workshop Series 

We are excited to announce a series of NVIDIA-led workshops designed to enhance your expertise in GPU computing. Whether you're a beginner or looking to deepen your skills, these sessions offer valuable insights and hands-on learning opportunities. Workshops are expected to be held on a monthly basis.  

NOTE: This event is open to Stanford and NVIDIA affiliates only.