Running Large Scale Training on a Supercomputer

Sam Foreman, ALCF
Eliu Huerta, Argonne National Laboratory
STS Foreman Session Graphic

Trainees will combine data pipeline and parallel training from previous sessions to train a modern classification network on a supercomputer.

Dr. Eliu Huerta will also speak about the work he does at Argonne AI4Physics.

About the Speakers

Sam Foreman is a computational scientist with a background in high energy physics, currently working as a postdoc in the ALCF. He is generally interested in the application of machine learning to computational problems in physics, particularly within the context of high-performance computing. Sam's current research focuses on using deep generative modeling to help build better sampling algorithms for simulations in lattice gauge theory.

Eliu Huerta is Lead for Translational AI and Computational Scientist in the Data Science and Learning Division at Argonne National Laboratory. He is a theoretical astrophysicist, mathematician and computer scientist with broad research interests. He has done pioneering work at the interface of physics-inspired AI, scientific visualization and extreme scale computing for multi-messenger astrophysics, cosmology, observational astronomy, and large scale simulations that describe multi-scale and multi-physics phenomena. Huerta received a Master of Advanced Study in Applied Mathematics and Theoretical Physics and a PhD in Theoretical Astrophysics from the University of Cambridge, United Kingdom. He leads several NSF- and DOE-funded interdisciplinary and multi-institutional projects that focus on disruptive AI applications and advanced computing for big-data experiments. He enjoys doing translational AI research across disciplines, industry, finance and tech.