Emerging Processor Architectures for Deep Learning: Options and Trade-offs

Summit Track: 
Enabling Technologies

In the past year, numerous new processor architectures for machine learning have emerged. Many of these focus on edge applications, reflecting the growing demand for deploying machine learning outside of data centers. This intensive focus on processor architecture innovation comes at a perfect time in light of the slowing progress in silicon fabrication technology and the massive opportunities for deployment of AI applications using vision and other sensors. In this presentation, we will explore the architectural concepts underlying these diverse processors and analyze their suitability for various applications. We will derive the performance bounds of each architecture approach and provide insights on the practical deployment of machine learning using these specialized architectures. In addition, using a case study we will explore the opportunities enabled through designing neural networks to exploit specialized processor architectures.

Speaker(s):

Orr Danon

CEO, Hailo

Orr Danon is co-founder and CEO of Hailo Technologies. Prior to starting Hailo, Orr spent a decade as a group leader in a leading technological unit of the Israeli Defense Forces, where he led some of the largest and most complex interdisciplinary projects in the Israeli intelligence community. For this work, Orr received the Israel Defense Award from the President of Israel and the Creative Thinking Award from the Head of Military Intelligence. Orr earned a B.Sc. and physics and mathematics from the Hebrew University as part of the ”Talpiot” program and an M.Sc. in electrical engineering (cum laude) from Tel Aviv University.

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