Distributed Training & Marlowe Multi-GPU Best Practices

Wednesday, May 21, 2025 | 2:00 - 3:30 PM PDT CoDa Building, Rm E401, 4th Floor

Abstract

This training focuses on efficient strategies for using multiple GPUs and nodes. We will overview how to deploy strategies of data parallelism and model parallelism to scale to multiple GPUs, enabling faster training times and better model performance.

Speaker

Aastha Jhunjhunwala is a Solutions Architect in the NVIDIA AI Enterprise team working with customers across different industries. She helps customers build optimized generative applications by leveraging the NVIDIA hardware and software stack.

Open to Stanford and NVIDIA affiliates.

Part of the ongoing NVIDIA & Marlowe seminar series.