On-chip photoelectric hybrid convolutional accelerator based on Bragg grating array

IF 4.4 2区物理与天体物理 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Results in Physics Pub Date : 2024-09-11 DOI:10.1016/j.rinp.2024.107968

Kaiteng Cai , Liqi Chen , Yunming Zhang , Juncheng Wang , Wei Lin , Shaoxiang Duan , Bo Liu

引用次数: 0

Abstract

We propose an on-chip photoelectric hybrid convolution accelerator based on Bragg grating array. The weight of the convolution kernel can be adjusted by controlling the central wavelengths of the Bragg grating array. We conducted simulation verification of the functionality and scalability of this on-chip photoelectric hybrid convolution accelerator. Subsequently, we constructed a neural network model to conduct handwritten digit classification simulations using this accelerator, achieving a simulation accuracy of 93.99%. Finally, the concept of the proposed on-chip photoelectric hybrid convolution accelerator is successfully verified. Due to the merits of Bragg grating, the proposed scheme paves the way for realizing high-performance on-chip optical neural networks.

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基于布拉格光栅阵列的片上光电混合卷积加速器

我们提出了一种基于布拉格光栅阵列的片上光电混合卷积加速器。卷积核的权重可通过控制布拉格光栅阵列的中心波长来调整。我们对这种片上光电混合卷积加速器的功能和可扩展性进行了仿真验证。随后，我们构建了一个神经网络模型，利用该加速器进行了手写数字分类模拟，模拟准确率达到 93.99%。最后，成功验证了所提出的片上光电混合卷积加速器的概念。由于布拉格光栅的优点，所提出的方案为实现高性能片上光神经网络铺平了道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Results in Physics MATERIALS SCIENCE, MULTIDISCIPLINARYPHYSIC-PHYSICS, MULTIDISCIPLINARY

CiteScore

8.70

自引率

9.40%

发文量

754

审稿时长

50 days

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