Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks

M. Tan; X. Xu; J. Wu; A. Boes; B. Corcoran; T. G. Nguyen; S. T. Chu; B. E. Little; R. Morandotti; A. Mitchell; D. G. Hicks; D. J. Moss

doi:10.1117/12.2584011

Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks

M. Tan, X. Xu, J. Wu, A. Boes, B. Corcoran, T. G. Nguyen, S. T. Chu, B. E. Little, R. Morandotti, A. Mitchell, D. G. Hicks, D. J. Moss

Electrical and Computer Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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- A chieving 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.

Original language	English
Title of host publication	Proceedings of SPIE, Smart Photonic and Optoelectronic Integrated Circuits XXIII
Editors	Sailing He, Laurent Vivien
Place of Publication	Bellingham WA USA
Publisher	SPIE - International Society for Optical Engineering
Number of pages	14
ISBN (Electronic)	9781510642164
ISBN (Print)	9781510642157
DOIs	https://doi.org/10.1117/12.2584011
Publication status	Published - 2021
Event	Smart Photonic and Optoelectronic Integrated Circuits XXIII 2021 - Online, United States of America Duration: 6 Mar 2021 → 11 Mar 2021 https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11690.toc (Proceedings)

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Publisher	SPIE - International Society for Optical Engineering
Volume	11690
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Smart Photonic and Optoelectronic Integrated Circuits XXIII 2021
Country/Territory	United States of America
Period	6/03/21 → 11/03/21
Internet address	https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11690.toc (Proceedings)

Keywords

Kerr micro-combs
micro-ring resonators
microwave photonics
Optical neural networks

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1117/12.2584011

Cite this

Tan, M., Xu, X., Wu, J., Boes, A., Corcoran, B., Nguyen, T. G., Chu, S. T., Little, B. E., Morandotti, R., Mitchell, A., Hicks, D. G., & Moss, D. J. (2021). Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks. In S. He, & L. Vivien (Eds.), Proceedings of SPIE, Smart Photonic and Optoelectronic Integrated Circuits XXIII Article 116900M (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11690). SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2584011

Tan, M. ; Xu, X. ; Wu, J. et al. / Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks. Proceedings of SPIE, Smart Photonic and Optoelectronic Integrated Circuits XXIII. editor / Sailing He ; Laurent Vivien. Bellingham WA USA : SPIE - International Society for Optical Engineering, 2021. (Proceedings of SPIE - The International Society for Optical Engineering).

@inproceedings{36d76fb9ce814d9aa8c5f4a305d56cc7,

title = "Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks",

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- A chieving 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. ",

keywords = "Kerr micro-combs, micro-ring resonators, microwave photonics, Optical neural networks",

author = "M. Tan and X. Xu and J. Wu and A. Boes and B. Corcoran and Nguyen, \{T. G.\} and Chu, \{S. T.\} and Little, \{B. E.\} and R. Morandotti and A. Mitchell and Hicks, \{D. G.\} and Moss, \{D. J.\}",

note = "Publisher Copyright: {\textcopyright} 2021 SPIE.; Smart Photonic and Optoelectronic Integrated Circuits XXIII 2021 ; Conference date: 06-03-2021 Through 11-03-2021",

year = "2021",

doi = "10.1117/12.2584011",

language = "English",

isbn = "9781510642157",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE - International Society for Optical Engineering",

editor = "Sailing He and Laurent Vivien",

booktitle = "Proceedings of SPIE, Smart Photonic and Optoelectronic Integrated Circuits XXIII",

address = "United States of America",

url = "https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11690.toc",

}

Tan, M, Xu, X, Wu, J, Boes, A, Corcoran, B, Nguyen, TG, Chu, ST, Little, BE, Morandotti, R, Mitchell, A, Hicks, DG & Moss, DJ 2021, Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks. in S He & L Vivien (eds), Proceedings of SPIE, Smart Photonic and Optoelectronic Integrated Circuits XXIII., 116900M, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11690, SPIE - International Society for Optical Engineering, Bellingham WA USA, Smart Photonic and Optoelectronic Integrated Circuits XXIII 2021, United States of America, 6/03/21. https://doi.org/10.1117/12.2584011

Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks. / Tan, M.; Xu, X.; Wu, J. et al.
Proceedings of SPIE, Smart Photonic and Optoelectronic Integrated Circuits XXIII. ed. / Sailing He; Laurent Vivien. Bellingham WA USA: SPIE - International Society for Optical Engineering, 2021. 116900M (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11690).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks

AU - Tan, M.

AU - Xu, X.

AU - Wu, J.

AU - Boes, A.

AU - Corcoran, B.

AU - Nguyen, T. G.

AU - Chu, S. T.

AU - Little, B. E.

AU - Morandotti, R.

AU - Mitchell, A.

AU - Hicks, D. G.

AU - Moss, D. J.

PY - 2021

Y1 - 2021

N2 - 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- A chieving 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.

AB - 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- A chieving 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.

KW - Kerr micro-combs

KW - micro-ring resonators

KW - microwave photonics

KW - Optical neural networks

UR - http://www.scopus.com/inward/record.url?scp=85105938940&partnerID=8YFLogxK

U2 - 10.1117/12.2584011

DO - 10.1117/12.2584011

M3 - Conference Paper

AN - SCOPUS:85105938940

SN - 9781510642157

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Proceedings of SPIE, Smart Photonic and Optoelectronic Integrated Circuits XXIII

A2 - He, Sailing

A2 - Vivien, Laurent

PB - SPIE - International Society for Optical Engineering

CY - Bellingham WA USA

T2 - Smart Photonic and Optoelectronic Integrated Circuits XXIII 2021

Y2 - 6 March 2021 through 11 March 2021

ER -

Tan M, Xu X, Wu J, Boes A, Corcoran B, Nguyen TG et al. Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks. In He S, Vivien L, editors, Proceedings of SPIE, Smart Photonic and Optoelectronic Integrated Circuits XXIII. Bellingham WA USA: SPIE - International Society for Optical Engineering. 2021. 116900M. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2584011

Single perceptron at 12 GigaOPs based on a microcomb for versatile, high-speed scalable, optical neural networks

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Cite this