利用高维光波和微波多域复用的高积分光子张量核心

IF 20.6 Q1 OPTICS Light-Science & Applications Pub Date : 2025-01-03 DOI:10.1038/s41377-024-01706-9
Xiangyan Meng, Nuannuan Shi, Guojie Zhang, Junshen Li, Ye Jin, Shiyou Sun, Yichen Shen, Wei Li, Ninghua Zhu, Ming Li
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引用次数: 0

摘要

人工神经网络模型中参数量的激增对传统的张量计算硬件提出了巨大的挑战。得益于光学多维信息熵,光学智能计算被用作解决电子计算新挑战的替代解决方案。这些限制,在器件尺寸和光子集成规模方面,阻碍了光学芯片的性能。本文介绍了一种基于单个微环谐振器(MRR)的超高计算密度光张量处理单元(OTPU)来应对这些挑战。通过多波长激光器的独立调谐,MRR的操作能力被精心安排,最终形成一个光学张量核心。该设计在微波的时间、波长和频率方面,通过光波和微波多域混合复用促进张量卷积运算的执行。实验结果表明,基于mrr的OTPU的计算密度达到了34.04 TOPS/mm2。此外,识别MNIST手写数字的准确率为96.41%。这些成果标志着高性能光张量处理芯片的实现取得了重大进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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High-integrated photonic tensor core utilizing high-dimensional lightwave and microwave multidomain multiplexing

The burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing hardware. Benefiting from the available optical multidimensional information entropy, optical intelligent computing is used as an alternative solution to address the emerging challenges of electrical computing. These limitations, in terms of device size and photonic integration scale, have hindered the performance of optical chips. Herein, an ultrahigh computing density optical tensor processing unit (OTPU), which is grounded in an individual microring resonator (MRR), is introduced to respond to these challenges. Through the independent tuning of multiwavelength lasers, the operational capabilities of an MRR are orchestrated, culminating in the formation of an optical tensor core. This design facilitates the execution of tensor convolution operations via the lightwave and microwave multidomain hybrid multiplexing in terms of the time, wavelength, and frequency of microwaves. The experimental results for the MRR-based OTPU show an extraordinary computing density of 34.04 TOPS/mm2. Additionally, the achieved accuracy rate in recognizing MNIST handwritten digits was 96.41%. These outcomes signify a significant advancement toward the realization of high-performance optical tensor processing chips.

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来源期刊
Light-Science & Applications
Light-Science & Applications 数理科学, 物理学I, 光学, 凝聚态物性 II :电子结构、电学、磁学和光学性质, 无机非金属材料, 无机非金属类光电信息与功能材料, 工程与材料, 信息科学, 光学和光电子学, 光学和光电子材料, 非线性光学与量子光学
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发文量
803
审稿时长
2.1 months
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