Easily Scalable Photonic Tensor Core Based on Tunable Units with Single Internal Phase Shifters

Author:

Huang Ying1ORCID,Yue Hengsong1,Ma Wei1,Zhang Yiyuan1,Xiao Yao2,Wang Weiping3,Tang Yong4,Hu Xiaoyan3,Tang He2,Chu Tao1ORCID

Affiliation:

1. College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 P. R. China

2. School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 P. R. China

3. Artificial Intelligence Institute China Electronics Technology Group Corporation Beijing 100086 P. R. China

4. School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 P. R. China

Abstract

AbstractPhotonic neural networks (PNNs) show tremendous potential for artificial intelligence applications due to their higher computational rates than their traditional electronic counterpart. However, the scale‐up of PNN relies on the number of cascaded computing units, which is limited by the accumulated transmission attenuation. Here, a topology of PNN with Mach–Zehnder interferometers based on a single‐tuned phase shifter that implements arbitrary nonnegative or real‐valued matrices for vector‐matrix multiplication is proposed. Compared with the universal matrix mesh, the new configuration exhibits two orders of magnitude lower optical path loss and a twofold reduction in the number of the tunable phase shifter. An 8 × 8 reconfigurable chip is designed and fabricated, and it is experimentally verified that the 2 × 4 nonnegative‐valued matrix and the 2 × 2 real‐valued matrix are implemented in the proposed topology. Higher than 85% inference accuracies are obtained in the Modified National Institute of Standards and Technology handwritten digit recognition tasks with these matrices in the PNNs. Therefore, with much lower optical path loss and comparable computing accuracy, the proposed PNN configuration can be easily scaled up to tackle higher dimensional matrix multiplication, which is highly desired in tasks like voice and image recognition.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3