International Workshop on A Strategic Initiative of Computing: Systems and Applications (SISA): Integrating HPC, Big Data, AI and Beyond
Professor William J. DallyChief Scientist and SVP of Research at NVIDIA
Professor, Computer Science, Stanford University
The Synergy of HPC and Deep Learning
Deep learning is emerging as a major application for high-performance computing. While training of deep neural networks (DNNs) places some unique demands on computing hardware its shares with mainstream HPC applications the need for high performance arithmetic, high memory bandwidth, and high-bandwidth, low-latency networks. Deep learning can also be used to enhance traditional HPC applications both by interpreting the results and by “learning” constituent equations. This talk will examine the common requirements of DL and HPC and applications of DL to HPC.
Bill is Chief Scientist and Senior Vice President of Research at NVIDIA Corporation and a Professor (Research) and former chair of Computer Science at Stanford University. Bill and his group have developed system architecture, network architecture, signaling, routing, and synchronization technology that can be found in most large parallel computers today. While at Bell Labs Bill contributed to the BELLMAC32 microprocessor and designed the MARS hardware accelerator. At Caltech he designed the MOSSIM Simulation Engine and the Torus Routing Chip which pioneered wormhole routing and virtual-channel flow control. At the Massachusetts Institute of Technology his group built the J-Machine and the M-Machine, experimental parallel computer systems that pioneered the separation of mechanisms from programming models and demonstrated very low overhead synchronization and communication mechanisms. At Stanford University his group has developed the Imagine processor, which introduced the concepts of stream processing and partitioned register organizations, the Merrimac supercomputer, which led to GPU computing, and the ELM low-power processor. Bill is a Member of the National Academy of Engineering, a Fellow of the IEEE, a Fellow of the ACM, and a Fellow of the American Academy of Arts and Sciences. He has received the ACM Eckert-Mauchly Award, the IEEE Seymour Cray Award, the ACM Maurice Wilkes award, and the IPSJ FUNAI Achievement Award. He currently leads projects on computer architecture, network architecture, circuit design, and programming systems. He has published over 200 papers in these areas, holds over 100 issued patents, and is an author of the textbooks, Digital Design: A Systems Approach, Digital Systems Engineering, and Principles and Practices of Interconnection Networks.