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I/O-efficient iterative matrix inversion with photonic integrated circuits

Author

Listed:
  • Minjia Chen

    (University of Cambridge)

  • Yizhi Wang

    (University of Cambridge)

  • Chunhui Yao

    (University of Cambridge)

  • Adrian Wonfor

    (University of Cambridge)

  • Shuai Yang

    (University of Cambridge)

  • Richard Penty

    (University of Cambridge)

  • Qixiang Cheng

    (University of Cambridge
    GlitterinTech Limited)

Abstract

Photonic integrated circuits have been extensively explored for optical processing with the aim of breaking the speed and energy efficiency bottlenecks of digital electronics. However, the input/output (IO) bottleneck remains one of the key barriers. Here we report a photonic iterative processor (PIP) for matrix-inversion-intensive applications. The direct reuse of inputted data in the optical domain unlocks the potential to break the IO bottleneck. We demonstrate notable IO advantages with a lossless PIP for real-valued matrix inversion and integral-differential equation solving, as well as a coherent PIP with optical loops integrated on-chip, enabling complex-valued computation and a net inversion time of 1.2 ns. Furthermore, we estimate at least an order of magnitude enhancement in IO efficiency of a PIP over photonic single-pass processors and the state-of-the-art electronic processors for reservoir training tasks and multiple-input and multiple-output (MIMO) precoding tasks, indicating the huge potential of PIP technology in practical applications.

Suggested Citation

  • Minjia Chen & Yizhi Wang & Chunhui Yao & Adrian Wonfor & Shuai Yang & Richard Penty & Qixiang Cheng, 2024. "I/O-efficient iterative matrix inversion with photonic integrated circuits," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50302-3
    DOI: 10.1038/s41467-024-50302-3
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    References listed on IDEAS

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