IEEE AP/CAS/ED/MTT/SSC Seminar

Title: Mixed-Signal Compute Fabrics for Deep Neural Networks

Agenda:
10:00 - 10:10am Sign-in and networking
10:10 - 11:15am Seminar and Q&A

Location: Qualcomm AZ-Auditorium (10155 Pacific Heights Blvd, San Diego, CA 92121)
Non-Qualcomm attendees: Please arrive 10-15 minutes early to find street parking or in nearby Qualcomm parking structures.

Cost: Free

RSVP (optional):

Abstract:
Deep neural networks have emerged as an important new driver for custom VLSI computing hardware in resource-constrained environments. In this context, this talk will review asymptotic limits of purely digital implementations and discuss the potential benefits of employing mixed analog/digital compute fabrics. Given that most deep neural networks are limited by memory access and data movement, the presentation emphasizes these aspects as lead-ins to memory-like and in-memory processing approaches. For the latter, we show that emerging RRAM-based implementations may achieve an array-level energy efficiency of more than 1 POps/s/W for 2-bit input/output activations.

Speaker biography:
Boris Murmann is a Professor of Electrical Engineering at Stanford University. He joined Stanford in 2004 after completing his Ph.D. degree in electrical engineering at the University of California, Berkeley in 2003. From 1994 to 1997, he was with Neutron Microelectronics, Germany, where he developed low-power and smart-power ASICs in automotive CMOS technology. Since 2004, he has worked as a consultant with numerous Silicon Valley companies. Dr. Murmann’s research interests are in mixed-signal integrated circuit design, with special emphasis on sensor interfaces, data converters and custom circuits for embedded machine learning. In 2008, he was a co-recipient of the Best Student Paper Award at the VLSI Circuits Symposium and a recipient of the Best Invited Paper Award at the IEEE Custom Integrated Circuits Conference (CICC). He received the Agilent Early Career Professor Award in 2009 and the Friedrich Wilhelm Bessel Research Award in 2012. He has served as an Associate Editor of the IEEE Journal of Solid-State Circuits, an AdCom member and Distinguished Lecturer of the IEEE Solid-State Circuits Society, as well as the Data Converter Subcommittee Chair and the Technical Program Chair of the IEEE International Solid-State Circuits Conference (ISSCC). He is the founding faculty co-director of the Stanford SystemX Alliance and the faculty director of Stanford's System Prototyping Facility (SPF). He is a Fellow of the IEEE.