In situ training with silicon photonics neural networks

Bhavin J. Shastri, Matthew J. Filipovich, Zhimu Guo, Paul R. Prucnal, Sudip Shekhar, Volker J. Sorger

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Deep learning hardware accelerators based on analog photonic networks are trained on standard digital electronics. We discuss on-chip training of neural networks enabled by a silicon photonic architecture for parallel, efficient, and fast data operations.

Original languageEnglish (US)
Title of host publication2022 Photonics North, PN 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665453011
StatePublished - 2022
Event2022 Photonics North, PN 2022 - Niagara Falls, Canada
Duration: May 24 2022May 26 2022

Publication series

Name2022 Photonics North, PN 2022


Conference2022 Photonics North, PN 2022
CityNiagara Falls

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Atomic and Molecular Physics, and Optics


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