TALK TITLE: Deep Learning Hardware: Past, Present, and Future
SPEAKER: Bill Dally, Chief Scientist and Senior Vice President of Research, NVIDIA
DATE: Tuesday, November 23rd 2021, 6pm PT (Pacific Timezone)
REGISTER: https://forms.gle/MEEu5KyQeTHt1L8P9
WEB SITE: https://site.ieee.org/scv/scv-corporate-liaison-program/
WATCH PAST TALKS: https://youtube.com/playlist?list=PLb8j28CYROlwx1sgQmFUw7uMD1GCXbpfS
SPONSORS: IEEE SCV Section’s Corporate Liaison Program, IEEE Computer Society SCV Chapter; IEEE Industry Engagement
ABSTRACT: The current resurgence of artificial intelligence is due to advances in deep learning. Systems based on deep learning now exceed human capability in speech recognition, object classification, and playing games like Go. Deep learning has been enabled by powerful, efficient computing hardware. The algorithms used have been around since the 1980s, but it has only been in the last decade – when powerful GPUs became available to train networks – that the technology has become practical. Advances in DL are now gated by hardware performance. This talk will review the current state of deep learning hardware and explore a number of directions to continue performance scaling in the absence of Moore’s Law. Topics discussed will include number representation, sparsity, memory organization, optimized circuits, and analog computation.
EXTRA THIS MONTH: consider submitting a paper to IEEE Computer Special Issue on Technology Predictions. Papers due December 1st. Phil Laplante and Dejan Milojicic guest editors. More info: https://www.computer.org/digital-library/magazines/co/call-for-papers-special-issue-on-technology-predictions
Best Regards,
Dejan Milojicic, IEEE Santa Clara Valley Section, Corporate Liaison Program Chair,
