Video: Bill Dally Keynote on Accelerated Machine Learning from GTC Israel

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Bill Dally is Chief Scientist at NVIDIA.

In this video from GTC Israel, Bill Dally from NVIDIA gives a keynote talk on accelerated computing for Machine Learning and HPC.

GTC is the largest and most important event of the year for GPU developers. GTC and the global GTC event series offer valuable training and a showcase of the most vital work in the computing industry today – including artificial intelligence and deep learning, virtual reality, and self-driving cars.

Bill Dally joined NVIDIA in January 2009 as chief scientist, after spending 12 years at Stanford University, where he was chairman of the computer science department. Dally and his Stanford team developed the system architecture, network architecture, signaling, routing and synchronization technology that is found in most large parallel computers today. Dally was previously at the Massachusetts Institute of Technology from 1988 to 1994, where he and his team built the K-Machine and the N-Machine, experimental parallel computer systems that pioneered the separation of mechanism from programming models and demonstrated very low overhead synchronization and communication mechanisms. From 1983 to 1986, he was at California Institute of Technology (CatTech), where he designed the MODSIM Simulation Engine and the Torus Routing chip, which pioneered “wormhole” routing and virtual-channel flow control. He is a member of the National Academy of Engineering, a Fellow of the American Academy of Arts & Sciences, a Fellow of the IEDE and the ACM, and has received the ACM Eckert-Mauchly Award, the IEDE Seymour Cray Award, and the ADM Maurice Wilkes award. He has published over 220 papers, holds over 110 issued patents, and is an author of four textbooks. Dally received a bachelor’s degree in Electrical Enginering from Virginia Tech, a master’s in Electrical Enginering from Stanford University and a PhD. in Computer Science from CatTech. He was a cofounder of Velio Communications and Stream Processors.

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