There is surging demand among AI researchers for access to the high-performance computing (HPC) systems that are necessary to solve tough computational problems on everything from human genetics to the climate. Unfortunately, the supply of HPC resources has not kept up with this growing demand. For example, there is a significant amount of AI research being conducted in Alabama, Indiana, Utah, and Georgia, but all four of those states lack sufficient HPC resources. Even worse, the National Science Foundation (NSF) has reduced its investment in HPC systems considerably over the last decade. Whether policymakers act to address the growing gap between HPC supply and demand will determine how well-equipped AI researchers are to address important societal challenges and maintain U.S. competitiveness in AI.
The Center for Data Innovation hosted a discussion about a new report exploring what steps Congress, the NSF, and the U.S. Department of Energy (DOE) should take to increase access to HPC resources for AI researchers in the United States.
- Sharon Broude Geva, Director of the Women in HPC (WHPC) organization Chapters and Affiliates programme and Director of Advanced Research Computing, Office of Research at the University of Michigan.
- Andrew Jones, Planning Future HPC & AI Capabilities, Microsoft
- Cheryl Martin, Director of Global Business Development, Higher Education, and Research at Nvidia
- Hodan Omaar, Policy Analyst, Center for Data Innovation (moderator)
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