Machine Learning and Science Forum — AI at the exascale

ML&Sci Forum

January 25, 2021
11:00am to 12:00pm
Virtual Participation

Machine Learning and Science Forum
Date: Monday, January 25, 2021
Time: 11:00 AM - 12:00 PM Pacific Time
Location: Participate remotely using this Zoom link
Speaker: Debbie Bard, Acting Group Lead, Data Science Engagement Group, NERSC 
Title: AI at the exascale 
Abstract: It is no coincidence that the rise of AI as a valuable tool for science has come at an interesting time for computing, where the end of Moore’s Law has meant that energy constraints are increasingly driving hardware innovation. AI is playing a growing role in shaping computing architecture, even at the largest scales. The US Department of Energy (DOE) recently announced the USA's first exascale supercomputers, coming in 2022 at a combined cost of $1.1B. These will be based on GPU architectures, and have been designed specifically for large-scale AI science applications that will be partly developed by the US DOE ExaLearn program, a new co-design center for exascale machine learning technologies. In addition, many other specialized energy-efficient architectures designed for AI workloads have emerged in the past few years, including FPGAs, custom ASICs like Google’s TPU and Graphcore, and neuromorphic machines. In this talk I will explore the interplay between energy-efficient hardware and the rise of AI as a serious factor in scientific computing. I will focus on the challenges and opportunities for AI in the exascale era, with a focus on applications to cosmology.

The BIDS Machine Learning and Science Forum (formerly the Berkeley Statistics and Machine Learning Forum) was launched in Spring 2018 and currently meets biweekly (during the spring and fall semesters) to discuss current applications across a wide variety of research domains in the physical sciences and beyond. These active sessions bring together domain scientists, statisticians, and computer scientists who are either developing state-of-the-art methods or are interested in applying these methods in their research. This Forum is organized by BIDS Faculty Affiliates Uroš Seljak (professor of Physics at UC Berkeley) and BIDS Research Affiliate Ben Nachman (Physicist at Lawrence Berkeley National Laboratory), Vanessa Böhm and Ben Erichson. All interested members of the UC Berkeley and Berkeley Lab communities are welcome and encouraged to attend. To receive email notifications about upcoming meetings, or to request more information, please contact berkeleymlforum@gmail.com.

Speaker(s)

Debbie Bard

Acting Group Lead, Data Science Engagement Group, NERSC