Paper Info
Title
Neural Network Calculations at the Speed of Light Using Optical Vector-Matrix Multiplication and Optoelectronic Activation
Abstract
With the rapid progress of the integrated nanophotonics technology, the optical neural network architecture has been widely investigated. Since the optical neural network can complete the inference processing just by propagating the optical signal in the network, it is expected more than one order of magnitude faster than the electronics-only implementation of artificial neural networks (ANN). In this paper, we first propose an optical vector-matrix multiplication (VMM) circuit using wavelength division multiplexing, which enables inference processing at the speed of light with ultra-wideband. This paper next proposes optoelectronic circuit implementation for batch normalization and activation function, which significantly improves the accuracy of the inference processing without sacrificing the speed performance. Finally, using a virtual environment for machine learning and an optoelectronic circuit simulator, we demonstrate the ultra-fast and accurate operation of the optical-electronic ANN circuit.
Year
DOI
Venue
2021
10.1587/transfun.2020KEP0016
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
Keywords
DocType
Volume
neural network, optical circuit, multi-layer perceptron, wavelength division multiplexing
Journal
E104A
Issue
ISSN
Citations 
11
0916-8508
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Naoki Hattori111.07
Jun Shiomi200.34
Yutaka Masuda313.10
Tohru Ishihara471987.96
Akihiko Shinya500.68
Masaya Notomi699.31