A review:Photonics devices,architectures,and algorithms for optical neural computing

• 作者: Shuiying Xiang Yanan Han Ziwei Song Xingxing Guo Yahui Zhang Zhenxing Ren Suhong Wang Yuanting Ma Weiwen Zou Bowen Ma Shaofu Xu Jianji Dong Hailong Zhou Quansheng Ren Tao Deng Yan Liu Genquan Han Yue Hao
• 来源期刊: 半导体学报（英文版）
• 年，卷（期）: 2021,（2）
• 所属期刊栏目: REVIEWS
• 页码范围: 66-82
• 页数: 17页
• 语种: 英文
• DOI: 10.1088/1674-4926/42/2/023105

摘要

The explosive growth of data and information has motivated various emerging non-von Neumann computational ap-proaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to the fascinat-ing advantages such as high speed,wide bandwidth,and massive parallelism.Here,we offer a review on the optical neural com-puting in our research groups at the device and system levels.The photonics neuron and photonics synapse plasticity are presented.In addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement learning.Finally,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives.