光电智能计算研究进展与挑战  

Advances and Challenges of Optoelectronic Intelligent Computing

作　　者：成骏伟 江雪怡 周海龙 董建绩 Cheng Junwei;Jiang Xueyi;Zhou Hailong;Dong Jianji(Wuhan National Laboratory for Optoelectronics,Huazhong University of Science and Technology,Wuhan 430074,Hubei,China;Optics Valley Laboratory,Wuhan 430074,Hubei,China)

机构地区：[1]华中科技大学武汉光电国家研究中心,湖北武汉430074 [2]湖北光谷实验室,湖北武汉430074

出　　处：《中国激光》2022年第12期321-333,共13页Chinese Journal of Lasers

基　　金：国家自然科学基金(62075075,U21A20511);湖北光谷实验室创新科研项目(OVL2021BG001)。

摘　　要：随着人工智能技术的高速发展,全球的计算量急剧增长,需要以快速、高效的方式处理海量数据,这对计算硬件的算力和能效提出了较高的要求。受限于电子器件的固有极限和冯·诺依曼架构,传统的电子计算在速度和能效方面遇到了难以突破的瓶颈。光电智能计算充分融合光学的多维复用、大带宽、低能耗等优势和电学的细粒度灵活控制特性,具有光算电控和软硬协同的特点,是一种更实用、更有竞争力的人工智能计算加速方案。回顾了光电智能计算的研究进展,探讨了目前用于光学信号处理和光学神经网络的主流计算架构在线训练算法以及算力、能效提升方面的挑战,并进行了展望。Significance Artificial intelligence (AI)is one of the most active research fields at present.The AI models,represented by artificial neural networks,are computational models that mimic the neural synaptic networks in the brain and have been widely used in areas such as computer vision,speech recognition,and automatic driving.In the last decade,the AI technologies have experienced an explosive growth and the global computational volume has increased dramatically.The urgent need to process massive data in a fast and efficient way has placed an urgent demand on the computing hardware in terms of computing capacity and energy efficiency.Restricted by the inherent limits of electronic devices and the von Neumann architecture,traditional electronic computing has encountered a bottleneck in terms of speed and energy efficiency,which is difficult to break through.Optoelectronic intelligent computing uses photons instead of electrons to perform computation,hence optoelectronic intelligent computing can significantly improve computing speed and energy efficiency by overcoming the inherent limits of electrons.Compared with electronic computing,optoelectronic intelligent computing fully combines the unique advantages of multi-dimensional multiplexing,large bandwidth,and low energy consumption of optics and the fine-grained and flexible control of electronics,which is a more practical and competitive solution for accelerating AI computing.Optoelectronic intelligent computing is particularly suitable for implementing large-scale neural networks containing a large number of neurons and synapses.Restricted by interconnection density and Joule heat,the processing speed of current neuromorphic electronic chips is basically limited to the MHz range,and the energy consumption per multiply accumulate (MAC)operation requires several picojoules.However,the neuromorphic computing hardware built from basic photonic devices,such as Mach-Zehnder interferometer (MZI)mesh and micro-ring resonator(MRR)array,requires only tens of femtojoules

关 键 词：光计算 光电智能计算 人工智能 计算加速 光学信号处理 光学神经网络 

分 类 号：TN45[电子电信—微电子学与固体电子学]