Power and Energy Efficiency in Hyper-Scale AI Data Centers

Abstract: We have been witnessing rapid growth of data centers as industry players race to develop AI models and applications. Our ability to improve power delivery to and energy efficiency of data centers will determine our ability to meet the AI application needs in the coming years. In this talk, I will discuss the main compute and data driving forces for increased data center scale and energy consumption as well as some potential approaches to mitigating their cost.

Bio: Wen-mei W. Hwu is a Senior Distinguished Research Scientist and Senior Director of Research at NVIDIA. He is also a Professor Emeritus and the Sanders-AMD Endowed Chair Emeritus of ECE at the University of Illinois at Urbana-Champaign after 34 years of service. His research is in the parallel architecture, algorithms, and infrastructure software for data intensive and computational intelligence applications. He served as the Illinois co-director of the IBM-Illinois Center for Cognitive Computing Systems Research Center (c3sr.com) from 2016 to 2020. He was a PI of the NSF Blue Waters supercomputer project and its associated PAID program for training science teams to use GPUs. For his research contributions, he received the ACM/IEEE Eckert-Mauchly Award, ACM SigArch Maurice Wilkes Award, the ACM Grace Murray Hopper Award, the IEEE Computer Society Charles Babbage Award, the ISCA Influential Paper Award, the MICRO Test-of-Time Award, the IEEE Computer Society B. R. Rau Award, the CGO Test-of-Time Award, several best paper awards, and the Distinguished Alumni Award in CS of the University of California, Berkeley. He is a Fellow of IEEE and ACM.