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High-order tensor flow processing using integrated photonic circuits.

Shaofu Xu1, Jing Wang1, Sicheng Yi1

  • 1State Key Laboratory of Advanced Optical Communication Systems and Networks, Intelligent Microwave Lightwave Integration Innovation Center (imLic), Department of Electronic Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China.

Nature Communications
|December 28, 2022
PubMed
Summary
This summary is machine-generated.

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This study introduces an integrated photonic tensor flow processor (PTFP) that processes high-order tensors directly in the optical domain. This novel approach avoids data duplication, enhancing computing efficiency for multiway signal processing applications.

Area of Science:

  • Photonics
  • Computer Science
  • Signal Processing

Background:

  • Traditional processors convert tensor convolutions to matrix multiplications, increasing computing throughput but also data duplication and memory consumption.
  • Efficient processing of multiway signals is crucial for advancements in various computational fields.

Purpose of the Study:

  • To propose and demonstrate an integrated photonic tensor flow processor (PTFP) that directly processes high-order tensors without digital data duplication.
  • To leverage optical domain capabilities for enhanced tensor computation.

Main Methods:

  • Developed an integrated photonic processor utilizing hybrid manipulation of optical wavelengths, space dimensions, and time delay steps.
  • Implemented a proof-of-concept experiment demonstrating PTFP functionalities with wavelength and delay step manipulation.

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  • Processed multi-channel images and videos at a 20 Gbaud modulation rate.

    • Main Results:

    • The PTFP directly represents and processes high-order tensors in the optical domain, eliminating the need for data duplication.
    • Achieved efficient processing of multi-channel images and videos.
    • Demonstrated a convolutional neural network for video action recognition on the processor with 97.9% accuracy.

    Conclusions:

    • The proposed PTFP offers a novel, efficient method for tensor analytics and multiway signal processing.
    • Optical domain processing of tensors presents a promising avenue for overcoming limitations of conventional digital processors.
    • The PTFP technology has potential applications in areas like artificial intelligence and real-time video analysis.