Integrated Neuromorphic Photonics: Synapses, Neurons, and Neural Networks

被引:52
作者
Guo, Xuhan [1 ]
Xiang, Jinlong [1 ]
Zhang, Yujia [1 ]
Su, Yikai [1 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, State Key Lab Adv Opt Commun Syst & Networks, Shanghai 200240, Peoples R China
来源
ADVANCED PHOTONICS RESEARCH | 2021年 / 2卷 / 06期
基金
中国国家自然科学基金; 国家重点研发计划; 上海市自然科学基金;
关键词
artificial intelligence; deep learning; neuromorphic networks; photonic integrated circuits; silicon photonics; PHASE-CHANGE MATERIALS; EXPERIMENTAL REALIZATION; ACTIVATION FUNCTIONS; INHIBITORY DYNAMICS; OPTICAL NEURON; LASERS; ENERGY; IMPLEMENTATION; OPERATION; PROGRESS;
D O I
10.1002/adpr.202000212
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Ever-growing demands of bandwidth, computing speed, and power consumption are now accelerating the transformation of computing research, as work-at-home becomes a new normal. Brain-inspired photonic neuromorphic computing for artificial intelligence is raising an urgent need, and it promises orders-of-magnitude higher computing speed and energy efficiency compared with digital electronic counterparts. Photonic neuromorphic networks combine the efficiency of neural networks based on a non-von Neumann architecture and the benefits of photonics to constitute a new computing paradigm. Herein, some recent advances in photonic neural networks are reviewed, including the concept, principle, key photonic components, and architectures that construct the neuromorphic systems, hoping to provide a better understanding of this emerging field.
引用
收藏
页数:29
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