Direct tensor processing with coherent light Article Swipe
Y. Zhang
,
Xiaobing Liu
,
Chenguang Yang
,
Jinlong Xiang
,
Hao Yan
,
Tianjiao Fu
,
Kaizhi Wang
,
Yikai Su
,
Zhipei Sun
,
Xuhan Guo
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2506.14277
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2506.14277
Tensor processing is the cornerstone of modern technological advancements, powering critical applications in data analytics and artificial intelligence. While optical computing offers exceptional advantages in bandwidth, parallelism, and energy efficiency, existing methods optimized for scalar operations struggle to efficiently handle tensor-based tasks, limiting their applicability in complex applications, such as neural networks. Here, we report Parallel Optical Matrix Matrix Multiplication (POMMM), a novel paradigm that enables fully parallel tensor processing through a single coherent light propagation. This approach addresses key limitations of current optical methods, scaling the performance with data dimension, while improving theoretical computational power and efficiency. We demonstrate its high consistency with GPU based matrix matrix multiplication across both real-valued and complex valued domains. Moreover, we showcase its adaptability, scalability, and versatility in tensor processing applications such as convolutional and vision transformer neural networks. Furthermore, we analyse the theoretical compatibility and efficiency of POMMM in relation to existing optical computing paradigms, highlighting its potential to outperform current state-of-the-art methods. By enabling a variety of computational tasks and supporting multi2 wavelength and large-scale expansion, POMMM provides a scalable, high-efficient foundation for advancing next-generation optical computing.
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- http://arxiv.org/abs/2506.14277
- https://arxiv.org/pdf/2506.14277
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Direct tensor processing with coherent lightWork title
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enPrimary language
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2025Year of publication
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2025-06-17Full publication date if available
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Y. Zhang, Xiaobing Liu, Chenguang Yang, Jinlong Xiang, Hao Yan, Tianjiao Fu, Kaizhi Wang, Yikai Su, Zhipei Sun, Xuhan GuoList of authors in order
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https://arxiv.org/abs/2506.14277Publisher landing page
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