模拟光计算推动人工智能发展

工程（英文） ›› 2022, Vol. 10 ›› Issue (3) : 133 -145. DOI: 10.1016/j.eng.2021.06.021

研究论文

模拟光计算推动人工智能发展

吴嘉敏 ^a^,^b^,^c^,^d^,^* ,
林星 ^b^,^d^,^e^,^* ,
郭雨晨 ^b^,^c^,^* ,
Junwei Liu ^f ,
方璐 ^b^,^c^,^e ,
Shuming Jiao ^g ,
戴琼海 ^a^,^b^,^c^,^d

作者信息 +

Analog Optical Computing for Artificial Intelligence

Jiamin Wu ^a^,^b^,^c^,^d^,^* ,
Xing Lin ^b^,^d^,^e^,^* ,
Yuchen Guo ^b^,^c^,^* ,
Junwei Liu ^f ,
Lu Fang ^b^,^c^,^e ,
Shuming Jiao ^g ,
Qionghai Dai ^a^,^b^,^c^,^d

Author information +

文章历史 +

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摘要

人工智能（AI）技术正在飞速发展并已在各行各业得到了广泛的应用，但大数据的爆炸式增长使其在硬件的处理速度和功耗方面面临了前所未有的严峻挑战。而光计算恰好利用光子的特性，包括宽带、低延迟和高能效，为解决这一瓶颈提供了一个独特的视角。本文介绍了不同AI 模型的光计算的最新研究进展，包括前馈神经网络、蓄水池计算和脉冲神经网络（SNN）。集成光子器件的最新进展和AI 的兴起为光计算在实际应用中的再次崛起创造了良好的发展机遇。这项浩大的工程需要不同领域多学科的交叉来实现。本文综述了近年来该领域的最前沿研究成果，讨论了目前相关技术的可用性，并指出了从不同方面推进该领域发展所面临的挑战。我们预计实际AI 应用所需的大规模集成光电子处理器时代，将很快以光电混合框架的形式到来。

Abstract

The rapid development of artificial intelligence (AI) facilitates various applications from all areas but also poses great challenges in its hardware implementation in terms of speed and energy because of the explosive growth of data. Optical computing provides a distinctive perspective to address this bottleneck by harnessing the unique properties of photons including broad bandwidth, low latency, and high energy efficiency. In this review, we introduce the latest developments of optical computing for different AI models, including feedforward neural networks, reservoir computing, and spiking neural networks (SNNs). Recent progress in integrated photonic devices, combined with the rise of AI, provides a great opportunity for the renaissance of optical computing in practical applications. This effort requires multidisciplinary efforts from a broad community. This review provides an overview of the state-of-the-art accomplishments in recent years, discusses the availability of current technologies, and points out various remaining challenges in different aspects to push the frontier. We anticipate that the era of large-scale integrated photonics processors will soon arrive for practical AI applications in the form of hybrid optoelectronic frameworks.