tinyML Summit 2022: Next-Generation Deep-Learning Accelerators: From Hardware to System

tinyML Summit 2022
Next-Generation Deep-Learning Accelerators: From Hardware to System
Sophia SHAO, Assistant Professor of Electrical Engineering and Computer Sciences, University of California, Berkeley
Machine learning is poised to substantially change society in the next 100 years, just as how electricity transformed the way industries functioned in the past century. In particular, deep learning has been adopted across a wide variety of industries, from computer vision, natural language processing, and autonomous driving, to robotic manipulation. Motivated by the high computational requirement of deep learning, there has been a large number of novel deep-learning accelerators proposed in academia and industry to meet the performance and efficiency demands of deep-learning applications. In this talk, I will discuss challenges and opportunities for the next generation of deep-learning accelerators, with a special focus on system-level implications of designing, integrating, and scheduling of future deep-learning accelerators.

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