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基于超材料的电磁神经网络研究进展

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随着人工智能技术的广泛应用,面向智能计算的算力需求呈井喷式增长.目前芯片的快速发展已经逼近其工艺制程的瓶颈,同时功耗也不断增加,因此高速、高能效的智能计算硬件研究是一个重要方向.以光子电路神经网络和全光衍射神经网络为代表的计算架构因其计算快、功耗低等优势而受到广泛关注.该文回顾了光神经网络的代表性工作,通过3维衍射神经网络和光神经网络芯片化发展两条主线进行介绍,同时,针对光学衍射神经网络和光子神经网络芯片面临的瓶颈和挑战,如网络规模和集成度等,分析比较它们的特点、性能和各自的优劣势.其次,考虑到通用化的发展需求,该文进一步讨论神经形态计算硬件的可编程设计,并在各个部分中介绍了一些可编程神经网络的代表性工作.除了光波段的智能神经网络,本文还讨论了微波衍射神经网络的发展和应用,展示了其可编程能力.最后介绍智能神经形态计算的未来方向和发展趋势,及其在无线通信、信息处理和传感方面的潜在应用.
Research Progress of Electromagnetic Neural Network Based on Metamaterials
With the widespread application of artificial intelligence technology,the demand for computing power for intelligent computing has grown exponentially.At present,the rapid development of chips has approached the bottleneck of its manufacturing process,and power consumption is also increasing.Therefore,research on high-speed,energy-efficient intelligent computing hardware is an important direction.Computing architectures represented by photonic circuit neural networks and all-optical diffraction neural networks have received widespread attention due to their advantages such as fast calculation and low power consumption.This article reviews the representative work of optical neural networks,and introduces it through the two main lines of development of three-dimensional diffractive neural networks and optical neural network chips.At the same time,it focuses on the bottlenecks and challenges faced by optical diffractive neural networks and photonic neural network chips,such as network scale and Integration degree,etc.,analyzes and compares their characteristics,performance and respective advantages and disadvantages.Secondly,taking into account the development needs of generalization,this article further discusses the programmable design of neuromorphic computing hardware,and introduces some representative work on programmable neural networks to each part.In addition to intelligent neural networks in the optical band,this article also discusses the development and application of microwave diffraction neural networks and demonstrates their programmability.Finally,the future direction and development trends of intelligent neuromorphic computing are introduced,as well as its potential applications in wireless communications,information processing and sensing.

MetamaterialsOptical diffractive neural networkElectromagnetic neural networkIntelligent computing

马骞、冯紫瑞、高欣欣、顾泽、游检卫、崔铁军

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东南大学毫米波国家重点实验室 南京 210096

东南大学电磁空间研究院 南京 210096

香港城市大学太赫兹毫米波国家重点实验室 香港 999077

超材料 全光衍射神经网络 电磁神经网络 智能计算

国家自然科学基金国家自然科学基金国家自然科学基金江苏省自然科学基金江苏省前沿引领技术基础研究专项中央高校基本科研业务费专项中央高校基本科研业务费专项中央高校基本科研业务费专项

623011476228810192167202BK20230822BK202120022242023K50022242018R300012242022R20017

2024

10.11999/JEIT231285

电子与信息学报
中国科学院电子学研究所 国家自然科学基金委员会信息科学部

电子与信息学报

CSTPCD北大核心
影响因子：1.302
ISSN：1009-5896
年,卷(期)：2024.46(5)