Massively-parallel Amplitude-Only Fourier Optical Convolutional Neural Network

Mario Miscuglio; Zibo Hu; Shurui Li; Jonathan K. George; Roberto Capanna; Hamed Dalir; Philippe M. Bardet; Puneet Gupta; Volker J. Sorger

doi:10.1364/CLEO_SI.2021.AW3E.5

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2021),
paper AW3E.5
•https://doi.org/10.1364/CLEO_SI.2021.AW3E.5

Massively-parallel Amplitude-Only Fourier Optical Convolutional Neural Network

Mario Miscuglio, Zibo Hu, Shurui Li, Jonathan K. George, Roberto Capanna, Hamed Dalir, Philippe M. Bardet, Puneet Gupta, and Volker J. Sorger

CLEO: Science and Innovations 2021

San Jose, California United States
9–14 May 2021
ISBN: 978-1-943580-91-0

From the session
A&TTR on Integrated Photonics in Neural Networks II (AW3E)

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M. Miscuglio, Z. Hu, S. Li, J. K. George, R. Capanna, H. Dalir, P. M. Bardet, P. Gupta, and V. J. Sorger, "Massively-parallel Amplitude-Only Fourier Optical Convolutional Neural Network," in Conference on Lasers and Electro-Optics, J. Kang, S. Tomasulo, I. Ilev, D. Müller, N. Litchinitser, S. Polyakov, V. Podolskiy, J. Nunn, C. Dorrer, T. Fortier, Q. Gan, and C. Saraceno, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper AW3E.5.

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Abstract

Here we introduce a novel amplitude-only Fourier-optical processor paradigm and demonstrate a prototype system capable of processing large-scale ~(2,000x1,000) matrices in a single time-step and 100 microsecond-short latency, for accelerating machine-learning applications.

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