Hybrid Computing for Scientific Simulations - Machine Learning in Science

This is a joint event with the Machine Learning Society (https://www.meetup.com/machine-learning-society/events/238346252/):

From biology and chemistry to high-energy and nuclear physics, scientists have come to rely on accurate models of physical phenomena to understand the world we live in. Today, there is an A.I. renaissance: machine learning algorithms and massively parallel processing (utilizing GPUs) are altering the scientific landscape

In this presentation, Rob Farber and Greg Scantlen will discuss the key advantages of hybrid computing and breakthrough methodologies in science and machine learning with the Simul8 HPC Environment. They will review emerging technologies like NVLink and High Bandwidth Memory which enable new capabilities for A.I. assisted High Performance Computing.

Speaker Bio: Rob Farber (http://www.techenablement.com/rob-farber/)

Rob was a staff scientist in the theoretical division at Los Alamos where he did basic research that established the machine and deep learning technology now used in the Internet and self-driving cars. He has been on staff at Berkeley, and other organizations around the world. Mr. Farber co-founded two startups with successful exits, one of which was a computational drug discovery company that utilized machine learning. Rob travels the world and is globally published. His latest book, Parallel Programming with OpenACC is available in English and will soon be available in Chinese as well. He works closely with major semiconductor companies including: NVIDIA, Intel, IBM, and ARM.