Large-Scale Optical Neural-Network Accelerators based on Coherent Detection

Ryan Hamerly; Alex Sludds; Liane Bernstein; Marin Soljačić; Dirk Englund

doi:10.1364/CLEO_AT.2019.JF2F.5

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2019),
paper JF2F.5
•https://doi.org/10.1364/CLEO_AT.2019.JF2F.5

Large-Scale Optical Neural-Network Accelerators based on Coherent Detection

Ryan Hamerly, Alex Sludds, Liane Bernstein, Marin Soljačić, and Dirk Englund

CLEO: QELS_Fundamental Science 2019

San Jose, California United States
5–10 May 2019
ISBN: 978-1-943580-57-6

From the session
Symposium on Deep-learning Photons: Where Machine Learning & Photonics Intersect II (JF2F)

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R. Hamerly, A. Sludds, L. Bernstein, M. Soljačić, and D. Englund, "Large-Scale Optical Neural-Network Accelerators based on Coherent Detection," in Conference on Lasers and Electro-Optics, OSA Technical Digest (Optica Publishing Group, 2019), paper JF2F.5.

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Abstract

We present a coherent optical neural-network accelerator based on homodyne detection that is scalable to large (N > 1000) networks, and analyze the fundamental quantum limits to its energy efficiency.

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