Hardware-Software Co-Design of Sustainable AI: Neuromorphic Computing and Beyond

Join us at 10 AM in RUCH 103 for a presentation from ECE Faculty Candidate Sangmin Yoo.

The relentless pursuit for AI is rapidly producing advanced algorithms and models, and an abundance of data, which on the other hand causes unsustainable power consumption projections to run. To sustain the AI advance, there is an urgent demand for better power-efficiency in both hardware and algorithms. In this talk, I discuss novel hardware-aware algorithms and algorithm-aware hardware designs that maximize each other’s utility. The approach covers the full stack of AI computing, including: (1) devices that natively possess information through internal dynamics, (2) device physics-enabled algorithms and architectures for brain-inspired neuromorphic systems and AI accelerators, and (3) cognitive algorithms enabling more efficient and better AI inference for large language models. These innovations collaboratively help accomplish the dream of “Artificial Intelligence” that thinks, learns, and operates as the name truly means, beyond the current stage of “machine intelligence”.

Speaker Bio

Sangmin Yoo is a Ph.D. candidate in the department of electrical and computing engineering at the University of Michigan. He received his B.S. in semiconductor systems engineering from Sungkyunkwan University in South Korea in 2016 and worked as a process integration engineer for Samsung Semiconductor Research (2016-2019). He then moved to the University of Michigan for his doctoral study and research.