Speaker's Bio: Dr. Jae-sun Seo is an Associate Professor at the School of ECEE at Arizona State University. His research interests include efficient hardware design of machine learning / neuromorphic algorithms and integrated power management. He was a recipient of the IBM Outstanding Technical Achievement Award (2012), NSF CAREER Award (2017), and Intel Outstanding Researcher Award (2021).
Talk Abstract: Artificial intelligence (AI) and deep learning have been successful across many practical applications, but state-of-the-art algorithms require an enormous amount of computation, memory, and on-/off-chip communication. To bring expensive algorithms to a low-power processor, a number of digital CMOS ASIC solutions have been previously proposed, but limitations still exist on memory access and footprint. To improve upon the conventional row-by-row operation of memories, “in-memory computing (IMC)” designs have been proposed, which performs analog computation inside memory arrays by asserting multiple or all rows simultaneously. In this talk, we will present circuit-level, system-level, and algorithm-level techniques for designing SRAM IMC-based AI systems with high energy efficiency (compared to digital ASIC), high accuracy (similar to software baseline), and enhanced robustness (against adversarial attacks).
Organizer: Dr. Ramtin Zand
Seminar Webpage: www.icaslab.com/Seminar