Scientific Computing With NVIDIA Grace and the Arm Software Ecosystem
, Principal Technical Product Manager, Datacenter CPU Software, NVIDIA
, Research Associate/Manager, University of Texas at Austin
Join us for a demonstration of top ML frameworks, HPC applications, and tools for data science on NVIDIA's Grace Hopper and Grace CPU Superchip. These superchips are the cornerstones of versatile and power-efficient supercomputers worldwide that combine Grace CPUs, Hopper GPUs, and extreme scale networking technology, in a standards-compliant server. We'll showcase recent results from key applications like PyTorch, JAX, WRF, GROMACS, and NAMD. We'll also provide lessons learned and experiences to help guide developers creating their own applications for NVIDIA Grace superchips. We'll conclude with a general guide to porting to NVIDIA Grace and links to downloadable resources and tutorials to help replicate our results. This session is a strong starting point for anyone looking to understand, and develop for, NVIDIA Grace Hopper or the Grace CPU Superchip.