This talk will discuss the evolution of GPU computing over the last ten years from computer gaming to high performance and scientific computing to most recently self-driving cars and speech recognition in the data center. Along the way, there have been many challenges and innovations in hardware architecture, memory technology, power efficiency, resiliency and programming models. Most recently, deep learning have emerged as a dominant workload that is driving many of the new applications. This new workload shares many aspects of prior applications while at the same time introducing new and unique computational demands that are driving next-generation design.
Michael Lightstone is currently VP of GPU Architecture at Nvidia. His team designs next-generation GPU HW for applications ranging from high performance computing to deep learning to virtual reality with a focus on performance, programmability, efficiency and resiliency Michael obtained his Ph.D. in ECE from the University of California at Santa Barbara and a B.S. in ECE from the University of Illinois at Urbana-Champaign.