矩阵乘法
光子学
计算机科学
乘法(音乐)
信号处理
光学计算
多路复用
电信
数字信号处理
电子工程
物理
光学
工程类
计算机硬件
量子
声学
量子力学
作者
Hailong Zhou,Jianji Dong,Junwei Cheng,Wenchao Dong,Chaoran Huang,Yichen Shen,Qiming Zhang,Miṅ Gu,Chao Qian,Hongsheng Chen,Zhichao Ruan,Chi Zhang
标识
DOI:10.1038/s41377-022-00717-8
摘要
Matrix computation, as a fundamental building block of information processing in science and technology, contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms. Photonic accelerators are designed to accelerate specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for computing resources and capacity. Photonic matrix multiplication has much potential to expand the domain of telecommunication, and artificial intelligence benefiting from its superior performance. Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors. In this review, we first introduce the methods of photonic matrix multiplication, mainly including the plane light conversion method, Mach-Zehnder interferometer method and wavelength division multiplexing method. We also summarize the developmental milestones of photonic matrix multiplication and the related applications. Then, we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years. Finally, we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.
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