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

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Researchers developed an ultrahigh-density optical tensor processing unit (OTPU) using microring resonators. This optical computing approach overcomes limitations of electrical computing for artificial neural networks, achieving high accuracy in digit recognition.

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Area of Science:

  • Photonics and Artificial Intelligence
  • Optical Computing Hardware

Background:

  • Growing parameter counts in neural networks challenge traditional tensor computing hardware.
  • Optical intelligent computing offers a promising alternative to electrical computing, but faces limitations in device size and photonic integration.
  • Existing optical chip designs struggle to meet the demands of complex AI computations.

Purpose of the Study:

  • To introduce an ultrahigh computing density optical tensor processing unit (OTPU) to address the limitations of current hardware.
  • To demonstrate a novel optical tensor core based on microring resonators (MRRs).
  • To enable efficient tensor convolution operations using hybrid lightwave and microwave multiplexing.

Main Methods:

  • Utilized individual microring resonators (MRRs) as the foundation for the optical tensor processing unit.
  • Orchestrated MRR capabilities through independent tuning of multiwavelength lasers to form an optical tensor core.
  • Implemented tensor convolution operations via hybrid multiplexing across time, wavelength, and microwave frequency domains.

Main Results:

  • Achieved an extraordinary computing density of 34.04 TOPS/mm² with the MRR-based OTPU.
  • Demonstrated a high accuracy rate of 96.41% in recognizing MNIST handwritten digits.
  • Validated the effectiveness of lightwave and microwave multidomain hybrid multiplexing for tensor operations.

Conclusions:

  • The developed MRR-based OTPU represents a significant advancement in optical tensor processing.
  • This technology offers a viable solution for high-performance optical chips in artificial intelligence applications.
  • The ultrahigh computing density and accuracy pave the way for next-generation AI hardware.