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Benjamin C. Lee (University of Pennsylvania): “Towards Sustainable Artificial Intelligence and Datacenters”
October 23 @ 12:00 PM - 1:15 PM
Abstract:
As the impact of artificial intelligence (AI) continues to proliferate, computer architects must assess and mitigate its environmental impact. This talk will survey strategies for reducing the carbon footprint of AI computation and datacenter infrastructure, drawing on data and experiences from industrial, hyperscale systems. First, we analyze the embodied and operational carbon implications of super-linear AI growth. Second, we re-think datacenter infrastructure and define a solution space for carbon-free computation with renewable energy, utility-scale batteries, and job scheduling. Finally, we develop strategies for datacenter demand response, incentivizing both batch and real-time workloads to modulate power usage in ways that reflect their performance costs. In summary, the talk provides a broad perspective on sustainable computing and outlines the many remaining directions for future work.
Biography:
Benjamin C. Lee is a Professor of Electrical and Systems Engineering and of Computer and Information Science at the University of Pennsylvania. He is also a visiting researcher at Google in the Global Infrastructure Group. Dr. Lee’s research focuses on computer architecture (microprocessors, memories, datacenters) and energy efficiency. He builds interdisciplinary links to machine learning and algorithmic game theory to better design and manage computer systems. His research on sustainable computing received an NSF Expedition in Computing award in 2024.
Dr. Lee was an Assistant and then Associate Professor at Duke University. He received his post-doctorate in Electrical Engineering at Stanford University, Ph.D. in Computer Science from Harvard University, and B.S. in Electrical Engineering and Computer Science from the University of California at Berkeley. He is an IEEE Fellow and ACM Distinguished Scientist.
Recording: https://drive.google.com/file/d/1yVTzbusDQ4KAVUhDIfsbB0Mz3ku7D8ot/view?usp=sharing
