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Presented by NVIDIA

Title of Presentation:  Using GPUs to accelerate HPC and Machine Learning

These Webinars are posted on the MSM YouTube Channel

Abstract

High Performance Computing (HPC) with GPUs can accelerate many areas of computational science, data science, and machine learning. By understanding the profile of different algorithms and workflows, GPUs can be leveraged to speed up many scientific experiments such as: training a neural network, ingesting/processing large-scale datasets, and supporting advanced visualization techniques. This talk will outline the capabilities that GPU computing provides to the research community, as well as provide an overview of some of the algorithms and software available to practitioners for leveraging GPUs. One package we focus on for this talk is RAPIDS, a library to accelerate Machine Learning workflows.”

Bios:

Jesse Tetreault - Jesse is a Solutions Architect working in Healthcare at NVIDIA, helping researchers accelerate Deep Learning and High Performance Computing workflows related to medical imaging. Prior to NVIDIA he received both a B.S. and M.S. in Computer Engineering from Clemson University focusing on Deep Learning for Computer Vision. He also co-instructs a course in Deep Learning for Medical Image Analysis at the National Institutes of Health.

Raghav Mani - Raghav manages Developer Relations at NVIDIA, focusing on Machine Learning use cases in Healthcare. Prior to NVIDIA, Raghav worked for 15 years at Epic leading different product & engineering teams. Most recently, he led a team of data scientists and engineers in building Epic’s ML platform on Azure.

This is part of a series of recordings for the ML-MSM Meeting, see complete list of Pre-Meeting Webinars