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With modern AI seemingly transforming all aspects of our modern society like magic, it is easy to forget the impacts such modern technology marvel is causing to our fragile environment. From massive industry-scale training of large neural networks of epic sizes, to the proliferation of folding AI inference in our everyday activities, AI applications are rapidly increasing the stress to our global energy and water infrastructure. The coming era of AI demands not only the smartest AI models, but also a new generation of sustainable AI mindset that rethinks the when and how to apply AI intelligence.
In this talk, Professor So will discuss one angle that addresses the “how” question with intelligent algorithm-architecture co-designed systems that reduce both energy consumption and computing latency using dynamic sparse processing. Sharing the same “more is less” principle, a series of works from a dynamic sparse processing system for event cameras to token-steering in modern diffusion models will be discussed. Together, these works illustrate that by doing a little bit more upfront intelligently, it is possible to drastically reduce the amount of work necessary to perform the same AI inference operation during run time without affecting the accuracy of a model. The results are solutions that not only are fast, but they are also orders of magnitude more energy-efficient than typical GPU-accelerated systems.
Professor Hayden So received his B.S., M.S., and Ph.D. degrees in electrical engineering and computer sciences from the University of California, Berkeley in 1998, 2000, and 2007, respectively. He is currently the Acting Director of the School of Innovation and Associate Professor in the Department of Electrical and Electronic Engineering, University of Hong Kong. He is also the co-director and founding member of the Joint Lab on Future Cities at the University of Hong Kong. His research focuses on highly efficient reconfigurable computing system designs and their applications. He is an IEEE Computer Society Distinguished Visitor and has been awarded the CODES+ISSS Test-of-Time award, in 2021, the IEEE-HKN C. Holmes MacDonald Outstanding Teaching Award, in 2021, the Croucher Innovation Award, in 2013, and the University Outstanding Teaching Award in 2012. He is an active member of the international reconfigurable computing community, having served as organizer and technical program chairs of many international conferences in the field, including FCCM, FPL, FPT, ASAP, ARC, HEART, ReConFig, and HiPEAC. He was a cofounder of the International Workshop on Overlay Architecture for FPGA (OLAF) and is a frequent reviewer for journals including ACM TRETS, ACM TACO, IEEE TPDS, etc.
Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
