Photonics and microwaves merge to improve computing flexibility

Hongwei Wang; Guangwei Hu

doi:10.1038/s41377-025-01933-8

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Photonics and microwaves merge to improve computing flexibility

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- Photonics and microwaves merge to improve computing flexibility
- Photonics and microwaves merge to improve computing flexibility
- Light: Science & Applications 2025年14卷第10期页码：2863-2864
- Affiliations：
  
  School of Electrical and Electronic Engineering, 50 Nanyang Avenue, Nanyang Technological University, Singapore 639798, Singapore
- Author bio：
  
  Guangwei Hu (guangwei.hu@ntu.edu.sg)
- Funds：
- DOI：10.1038/s41377-025-01933-8
  中图分类号：
- 网络出版：2025-09-04，
  
  纸质出版：2025-10-31
- Accepted：
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Hongwei Wang, Guangwei Hu. Photonics and microwaves merge to improve computing flexibility[J]. Light: Science & Applications, 2025,14(10):2863-2864.

Wang, H. W. & Hu, G. W. Photonics and microwaves merge to improve computing flexibility. Light: Science & Applications, 14, 2863-2864 (2025).
Hongwei Wang, Guangwei Hu. Photonics and microwaves merge to improve computing flexibility[J]. Light: Science & Applications, 2025,14(10):2863-2864. DOI： 10.1038/s41377-025-01933-8.

Wang, H. W. & Hu, G. W. Photonics and microwaves merge to improve computing flexibility. Light: Science & Applications, 14, 2863-2864 (2025). DOI： 10.1038/s41377-025-01933-8.

摘要

Abstract

In artificial neural networks

data structures usually exist in the form of vectors

matrices

or higher-dimensional tensors. However

traditional electronic computing architectures are limited by the bottleneck of separation of storage and computing

making it difficult to efficiently handle large-scale tensor operations. The research team has developed a photonic tensor processing unit based on a single microring resonator

which performs tensor convolution operations in multiple dimensions of time

wavelength

and microwave frequency by precisely adjusting the operating state of multi-wavelength lasers. This innovative design increases the photonic computing density to 34.04 TOPS/mm

significantly surpassing the performance level of existing photonic computing chips.

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references

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