ECE SEMINAR: Road to Resilient Autonomous Cars is Paved with Diverse Redundancy
LUNCH WILL BE SERVED AT 11:30
Deep neural networks use the computational power of massively parallel processors in applications such as autonomous driving. Autonomous driving demands resiliency (as in reliability, availability and safety) and performance (trillions of operations per second) to process sensor data with extreme accuracy. This talk examines various approaches to achieve resiliency in autonomous cars and makes the case for design diversity-based redundancy as a viable solution.
Nirmal R. Saxena currently leads NVIDIA's effort on HPC and Resilient Compute Architecture. Prior to NVIDIA (1984-2015), Nirmal held technical and management roles in several semiconductor, computer and networking companies. He was also associated with Stanford University's Center for Reliable Computing and EE Department (1991-2009). He taught courses in Logic Design, Computer Architecture, Fault-Tolerant Computing, and was co-investigator with Professor Edward J. McCluskey on DARPA's ROAR (Reliability Obtained through Adaptive Reconfiguration) project.
Nirmal received his BE ECE degree (1982) from Osmania University, India; MSEE degree (1984) from the University of Iowa; and Ph.D. EE degree (1991) from Stanford University. He is a Fellow of IEEE (2002) and was cited for his contributions to reliable computing.
ZOOM LINK: https://duke.zoom.us/j/96073755266?pwd=TjAzVHpFWlQyREs2cXRiUlp4N3Zhdz09