Paper
27 November 2023 Matrix convolutional operation architecture based on optical Fourier transform
Ning Shen, Changhe Zhou
Author Affiliations +
Abstract
In this paper, We propose a highly parallel optical matrix convolution architecture based on optical Fourier transform (OFT). The matrix multiply-accumulate (MAC) operations consists of matrix multiplication and addition. In the matrix multiplication section, the light intensity signals of matrix A and matrix B carried by two SLMs are used. Matrix C is obtained by matrix multiplication by projecting the uniform light intensity of matrix A onto matrix B through a Dammann grating (DG). The matrix C is received by a CMOS camera after a lens, and the spot array of matrix C is summed up, The convolution results of matrix A and B are obtained. This matrix convolution architecture provides an interesting method for large-scale matrix convolution. The optical matrix convolutional architecture has advantages such as high parallelism, high accuracy, and low power consumption. In the future, the optical computing will be perfectly applied in areas such as deep learning algorithms.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Ning Shen and Changhe Zhou "Matrix convolutional operation architecture based on optical Fourier transform", Proc. SPIE 12768, Holography, Diffractive Optics, and Applications XIII, 127680Z (27 November 2023); https://doi.org/10.1117/12.2687139
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KEYWORDS
Matrices

Convolution

Fourier transforms

Matrix multiplication

Optical matrix switches

Lens arrays

Optical computing

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