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作 者:Shaofu Xu Weiwen Zou 徐绍夫;邹卫文(State Key Laboratory of Advanced Optical Communication Systems and Networks,Intelligent Microwave Lightwave Integration Innovation Center,Department of Electronic Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
出 处:《Chinese Optics Letters》2021年第8期84-89,共6页中国光学快报(英文版)
基 金:supported by the National Key R&D Program of China (No.2019YFB2203700);the National Natural Science Foundation of China (No.61822508)。
摘 要:We propose an optical tensor core(OTC) architecture for neural network training. The key computational components of the OTC are the arrayed optical dot-product units(DPUs). The homodyne-detection-based DPUs can conduct the essential computational work of neural network training, i.e., matrix-matrix multiplication. Dual-layer waveguide topology is adopted to feed data into these DPUs with ultra-low insertion loss and cross talk. Therefore, the OTC architecture allows a large-scale dot-product array and can be integrated into a photonic chip. The feasibility of the OTC and its effectiveness on neural network training are verified with numerical simulations.
关 键 词:optical tensor core neural network training matrix multiplication homodyne detection dual-layer waveguides
分 类 号:TN491[电子电信—微电子学与固体电子学] TP183[自动化与计算机技术—控制理论与控制工程]
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