11 Tera-OPs/s photonic convolutional accelerator and deep optical neural network based on an integrated Kerr soliton crystal microcomb

Mengxi Tan; Xingyuan Xu; Yang Li; Yang Sun; Damien Hicks; Roberto Morandotti; Jiayang Wu; Arnan Mitchell; David J. Moss

doi:10.1117/12.2607906

4 March 2022 11 Tera-OPs/s photonic convolutional accelerator and deep optical neural network based on an integrated Kerr soliton crystal microcomb

Mengxi Tan, Xingyuan Xu, Yang Li, Yang Sun, Damien Hicks, Roberto Morandotti, Jiayang Wu, Arnan Mitchell, David J. Moss

Author Affiliations +

Proceedings Volume 11987, Laser Resonators, Microresonators, and Beam Control XXIV; 1198702 (2022) https://doi.org/10.1117/12.2607906
Event: SPIE LASE, 2022, San Francisco, California, United States

Abstract

Convolutional neural networks (CNNs), inspired by biological visual cortex systems, are a powerful category of artificial neural networks that can extract the hierarchical features of raw data to greatly reduce the network parametric complexity and enhance the predicting accuracy. They are of significant interest for machine learning tasks such as computer vision, speech recognition, playing board games and medical diagnosis. Optical neural networks offer the promise of dramatically accelerating computing speed to overcome the inherent bandwidth bottleneck of electronics. Here, we demonstrate a universal optical vector convolutional accelerator operating beyond 10 Tera-OPS (TOPS - operations per second), generating convolutions of images of 250,000 pixels with 8-bit resolution for 10 kernels simultaneously — enough for facial image recognition. We then use the same hardware to sequentially form a deep optical CNN with ten output neurons, achieving successful recognition of full 10 digits with 900 pixel handwritten digit images with 88% accuracy. Our results are based on simultaneously interleaving temporal, wavelength and spatial dimensions enabled by an integrated microcomb source. We show that this approach is scalable and trainable to much more complex networks for demanding applications such as unmanned vehicle and real-time video recognition.

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Citation Download Citation

Mengxi Tan, Xingyuan Xu, Yang Li, Yang Sun, Damien Hicks, Roberto Morandotti, Jiayang Wu, Arnan Mitchell, and David J. Moss "11 Tera-OPs/s photonic convolutional accelerator and deep optical neural network based on an integrated Kerr soliton crystal microcomb", Proc. SPIE 11987, Laser Resonators, Microresonators, and Beam Control XXIV, 1198702 (4 March 2022); https://doi.org/10.1117/12.2607906

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