@inproceedings{f58010f39fad4f4c972a9eebae6eb862,
title = "Silicon Photonic Neural Networks and Applications",
abstract = "Neuromorphic photonic processors promise orders of magnitude improvements in both speed and energy efficiency over purely digital electronic approaches. We will provide an overview of neuromorphic photonic systems and their application to machine learning and specifically deep learning inference with a hybrid digital electronics and analog photonics architecture based on silicon photonics. We will discuss scalability in the context of designing a full-scale neuromorphic photonic processing system, considering aspects such as signal integrity, noise, and hardware fabrication platforms.",
keywords = "Silicon photonics, machine learning, neuromorphic computing, optical computing, optical neural networks",
author = "Shastri, {B. J.} and Marquez, {B. A.} and Tait, {A. N.} and {Ferreira De Lima}, T. and Peng, {H. T.} and C. Huang and Prucnal, {P. R.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Photonics North, PN 2020 ; Conference date: 26-05-2020 Through 28-05-2020",
year = "2020",
month = may,
doi = "10.1109/PN50013.2020.9167001",
language = "English (US)",
series = "2020 Photonics North, PN 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 Photonics North, PN 2020",
address = "United States",
}