Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Time Wavelength Interleaving Perceptron at 12 Giga-Ops/s with a Kerr Soliton Crystal Microcomb for Optical Neural Networks

Version 1 : Received: 27 February 2021 / Approved: 1 March 2021 / Online: 1 March 2021 (14:56:09 CET)

How to cite: Tan, M.; Xu, X.; Moss, D. Time Wavelength Interleaving Perceptron at 12 Giga-Ops/s with a Kerr Soliton Crystal Microcomb for Optical Neural Networks. Preprints 2021, 2021030033 (doi: 10.20944/preprints202103.0033.v1). Tan, M.; Xu, X.; Moss, D. Time Wavelength Interleaving Perceptron at 12 Giga-Ops/s with a Kerr Soliton Crystal Microcomb for Optical Neural Networks. Preprints 2021, 2021030033 (doi: 10.20944/preprints202103.0033.v1).

Abstract

Optical artificial neural networks (ONNs) have significant potential for ultra-high computing speed and energy efficiency. We report a novel approach to ONNs that uses integrated Kerr optical micro-combs. This approach is programmable and scalable and is capable of reaching ultra-high speeds. We demonstrate the basic building block ONNs — a single neuron perceptron — by mapping synapses onto 49 wavelengths to achieve an operating speed of 11.9 x 109 operations per second, or Giga-OPS, at 8 bits per operation, which equates to 95.2 gigabits/s (Gbps). We test the perceptron on handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. By scaling the perceptron to a deep learning network using off-the-shelf telecom technology we can achieve high throughput operation for matrix multiplication for real-time massive data processing.

Subject Areas

microcombs; optical neural networks; perceptron

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.