SLIDE: Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning with Beidi Chen…

Today we’re joined by Beidi Chen, PhD student at Rice University. Beidi is part of the team that developed a cheaper, algorithmic, CPU alternative to state-of-the-art GPU machines. They presented their findings at NeurIPS 2019 and have since gained a lot of attention for their paper, SLIDE: In Defense of Smart Algorithms Over Hardware Acceleration for Large-Scale Deep Learning Systems. In this interview, Beidi shares how the team took a new look at deep learning with the case of extreme classification by turning it into a search problem and using locality-sensitive hashing. Check out the complete show notes at twimlai.com/talk/356.

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