光计算和光电智能计算研究进展  

Advances of Optical Computing and Optoelectronic Intelligent Computing

作　　者：张楠 黄郅祺 张子安 合聪 周辰 黄玲玲 王涌天 Zhang Nan;Huang Zhiqi;Zhang Zian;He Cong;Zhou Chen;Huang Lingling;Wang Yongtian(Beijing Engineering Research Center of Mixed Reality and Advanced Display,School of Optics and Photonics,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学光电学院北京市混合现实与新型显示工程技术研究中心,北京100081

出　　处：《中国激光》2024年第18期235-256,共22页Chinese Journal of Lasers

摘　　要：光计算是采用光信号承载计算数据并利用光学设备进行计算的方式,具有多维度、低延时、低功耗等显著优势。将光计算器件与现有电子计算设备相结合构成光电智能计算架构,有望突破摩尔定律的限制,满足人工智能大算力需求,颠覆传统电子计算范式,近年来在学术界和产业界引起越来越浓厚的研究兴趣。围绕光计算的两大分支——光学算子和光学神经网络展开综述,深入探讨各自的工作原理和特点、系统架构特征及应用场景。最后,对光计算和光电智能计算面临的挑战和未来的发展趋势进行展望。Significance Artificial intelligence(AI)is one of the most extensively investigated fields currently and has been widely applied in various fields such as agriculture,healthcare,home automation,and military.As its applications become increasingly complex,AI demands higher requirements on computing hardware in terms of computing power and energy efficiency.Currently,mainstream AI computations rely on integrated circuit chips such as central processing units(CPUs)or graphics processing units(GPUs),which are designed and manufactured using conventional microelectronic technologies,thus limiting their computing performance by the level of hardware-circuit integration density.According to Moore’s law,the integration density of circuits approximately doubles every 18 to 24 months.As Moore’s law reaches its limits and the demand for computing power continues to increase,researchers should develop transformative technologies that can overcome these challenges and shift computing to new paradigms.Optical(or photonic)computing,which uses optical fields as information carriers and optical devices to perform computations,has emerged as a promising and innovative field that can revolutionize various aspects of computing and information processing.It offers parallel and high-speed computation with significantly less energy consumption.Recently,interest toward optical computing and its interdisciplinary applications,i.e.,platforms,architectures,integrable hardware and protocols for storage,encryption,and data and signal processing,has increased.Optical computing paradigms can be categorized into two main types:optical operators and optical neural networks.For optical operators,the optical element functions as an independent optical computing unit to perform a specific operation.It can be combined with back-end electronic calculation components to form an optoelectronic intelligent computing architecture that jointly performs complex functions.For optical neural networks,similar to artificial neural networks,optical componen

关 键 词：光计算 光电智能计算 光学算子 光学神经网络 人工智能 

分 类 号：O436[机械工程—光学工程]