Numerical Simulation of a Photonic Tensor Core for the Hardware Acceleration of the Optical Matrix–Vector Multiplication

A realistic numerical model of a photonic tensor core based on the crossbar architecture with absorbing GeSbTe chalcogenide glass films as weight elements of a photonic matrix has been developed. The performance of the model for the matrix–vector multiplication has been demonstrated. The possibility of using the tensor core based on the implemented architecture in convolutional neural networks for image recognition tasks has been shown. Numerical simulations have been used for the first time to estimate the potential performance and energy efficiency of a photonic hardware accelerator, taking into account the modern experimental element base.

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Publication Details

Journal
Journal of Experimental and Theoretical Physics Letters
Published
2024-12-01
DOI
https://doi.org/10.1134/s0021364024603956
Citations
2
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.69
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article

Numerical Simulation of a Photonic Tensor Core for the Hardware Acceleration of the Optical Matrix–Vector Multiplication

Alexander S. Shorokhov, Andrey A. Fedyanin, G. A. Kolosov
2 citations
Journal of Experimental and Theoretical Physics Letters
Neural Networks and Reservoir Computing
0.69
article

Numerical Simulation of a Photonic Tensor Core for the Hardware Acceleration of the Optical Matrix–Vector Multiplication

Alexander S. Shorokhov, Andrey A. Fedyanin, G. A. Kolosov
article en
2 citations

Abstract

A realistic numerical model of a photonic tensor core based on the crossbar architecture with absorbing GeSbTe chalcogenide glass films as weight elements of a photonic matrix has been developed. The performance of the model for the matrix–vector multiplication has been demonstrated. The possibility of using the tensor core based on the implemented architecture in convolutional neural networks for image recognition tasks has been shown. Numerical simulations have been used for the first time to estimate the potential performance and energy efficiency of a photonic hardware accelerator, taking into account the modern experimental element base.

Journal of Experimental and Theoretical Physics LettersVol. 120(12)
Lomonosov Moscow State University (RU)
Openalex Percentile: Top 22%
Neural Networks and Reservoir Computing
0.69
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Numerical Simulation of a Photonic Tensor Core for the Hardware Acceleration of the Optical Matrix–Vector Multiplication — Alexander S. Shorokhov, Andrey A. Fedyanin, et al. · Journal of Experimental and Theoretical Physics Letters (2024) | TGRS Research Map | TGRS