Sachin Sapatnekar: Electronic Design Automation and Machine Learning - Building a Virtuous Cycle

The machine learning (ML) revolution has drastically changed computation, and old computation paradigms have been overhauled and supplemented with new approaches in the last few years. This talk focuses especially on the use of machine learning to solve problems in electronic design automation (EDA) -- and the use of EDA to better optimize machine learning hardware. The talk will overview various efforts that leverage ML in the EDA domains, including optimized power delivery, thermal analysis, and automated analog design, as well as EDA-driven optimizations for building better ML hardware. Together, these point the way to a virtuous cycle of design where ML and EDA work hand in hand.

Sachin S. Sapatnekar is the Henle Chair in ECE and Distinguished McKnight University Professor at the University of Minnesota. His current research interests include design automation methods for analog and digital circuits, circuit reliability, and algorithms and architectures for machine learning. He is a recipient of the NSF Career Award, the SRC Technical Excellence Award, the Semiconductor Industry Association’s University Research Award, and 12 Best Paper awards. He is a Fellow of the IEEE and the ACM.