1. Photonic Integrated Neuro-Synaptic Core for Convolutional Spiking Neural Network
- Author
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Xiang, Shuiying, Shi, Yuechun, Zhang, Yahui, Guo, Xingxing, Zheng, Ling, Han, Yanan, Zhang, Yuna, Song, Ziwei, Zheng, Dianzhuang, Zhang, Tao, Wang, Hailing, Zhu, Xiaojun, Chen, Xiangfei, Qiu, Min, Shen, Yichen, Zheng, Wanhua, and Hao, Yue
- Subjects
Physics - Optics - Abstract
Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture. Linear weighting and nonlinear spiking activation are two fundamental functions of a photonic spiking neural network (PSNN). However, they are separately implemented with different photonic materials and devices, hindering the large-scale integration of PSNN. Here, we propose, fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spiking activation based on a distributed feedback (DFB) laser with a saturable absorber (DFB-SA). A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation. Furthermore, a four-channel DFB-SA array is fabricated for realizing matrix convolution of a spiking convolutional neural network, achieving a recognition accuracy of 87% for the MNIST dataset. The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip.
- Published
- 2023