矩阵乘法
计算机科学
光子学
乘法(音乐)
基质(化学分析)
高效能源利用
光子集成电路
计算科学
计算机硬件
并行计算
物理
光学
电气工程
材料科学
量子力学
声学
量子
复合材料
工程类
作者
Rui Tang,Makoto Okano,Kasidit Toprasertpong,Shinichi Takagi,Dirk Englund,Mitsuru Takenaka
出处
期刊:Optics Express
[The Optical Society]
日期:2022-09-01
卷期号:30 (19): 33940-33940
被引量:5
摘要
Photonic integrated circuits (PICs) are emerging as a promising tool for accelerating matrix multiplications in deep learning. Previous PIC architectures, primarily focusing on the matrix-vector multiplication (MVM), have large hardware errors that increase with the device scale. In this work, we propose a novel PIC architecture for MVM, which features an intrinsically small hardware error that does not increase with the device scale. Moreover, we further develop this concept and propose a PIC architecture for the general matrix-matrix multiplication (GEMM), which allows the GEMM to be directly performed on a photonic chip with a high energy efficiency unattainable by parallel or sequential MVMs. This work provides a promising approach to realize a high fidelity and high energy efficiency optical computing platform.
科研通智能强力驱动
Strongly Powered by AbleSci AI