Hardware efficient learning on a 3-D optoelectronic neural system

Ashok V. Krishnamoorthy, Stephen A. Brodsky, Clark C. Guest, Gary C. Marsden, Matthias Blume, Gokce Yayla, Jean Merckle, Sadik Esener

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

1 Citation (Scopus)

Abstract

We discuss the Dual-Scale Topology Optoelectronic Processor (D-STOP) neural network, a scalable, optically interconnected neural network architecture. We present the tandem D-STOP system, which provides the connectivity needed for building fully-parallel neural networks with generic gradient-descent learning rules. We review the Content Addressable Network (CAN) learning algorithm, a discrete learning algorithm that provides accelerated learning with reduced hardware requirements. We then show how the CAN algorithm can be effectively mapped onto D-STOP, and we investigate associated optoelectronic hardware tradeoffs.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Neural Networks - Conference Proceedings
PublisherIEEE
Pages1998-2003
Number of pages6
Volume3
StatePublished - 1994
Externally publishedYes
EventProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA
Duration: Jun 27 1994Jun 29 1994

Other

OtherProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
CityOrlando, FL, USA
Period6/27/946/29/94

Fingerprint

Optoelectronic devices
Hardware
Topology
Neural networks
Learning algorithms
Network architecture

ASJC Scopus subject areas

  • Software

Cite this

Krishnamoorthy, A. V., Brodsky, S. A., Guest, C. C., Marsden, G. C., Blume, M., Yayla, G., ... Esener, S. (1994). Hardware efficient learning on a 3-D optoelectronic neural system. In IEEE International Conference on Neural Networks - Conference Proceedings (Vol. 3, pp. 1998-2003). IEEE.

Hardware efficient learning on a 3-D optoelectronic neural system. / Krishnamoorthy, Ashok V.; Brodsky, Stephen A.; Guest, Clark C.; Marsden, Gary C.; Blume, Matthias; Yayla, Gokce; Merckle, Jean; Esener, Sadik.

IEEE International Conference on Neural Networks - Conference Proceedings. Vol. 3 IEEE, 1994. p. 1998-2003.

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

Krishnamoorthy, AV, Brodsky, SA, Guest, CC, Marsden, GC, Blume, M, Yayla, G, Merckle, J & Esener, S 1994, Hardware efficient learning on a 3-D optoelectronic neural system. in IEEE International Conference on Neural Networks - Conference Proceedings. vol. 3, IEEE, pp. 1998-2003, Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7), Orlando, FL, USA, 6/27/94.
Krishnamoorthy AV, Brodsky SA, Guest CC, Marsden GC, Blume M, Yayla G et al. Hardware efficient learning on a 3-D optoelectronic neural system. In IEEE International Conference on Neural Networks - Conference Proceedings. Vol. 3. IEEE. 1994. p. 1998-2003
Krishnamoorthy, Ashok V. ; Brodsky, Stephen A. ; Guest, Clark C. ; Marsden, Gary C. ; Blume, Matthias ; Yayla, Gokce ; Merckle, Jean ; Esener, Sadik. / Hardware efficient learning on a 3-D optoelectronic neural system. IEEE International Conference on Neural Networks - Conference Proceedings. Vol. 3 IEEE, 1994. pp. 1998-2003
@inproceedings{8e927d2f462b4534926a56921db68d4e,
title = "Hardware efficient learning on a 3-D optoelectronic neural system",
abstract = "We discuss the Dual-Scale Topology Optoelectronic Processor (D-STOP) neural network, a scalable, optically interconnected neural network architecture. We present the tandem D-STOP system, which provides the connectivity needed for building fully-parallel neural networks with generic gradient-descent learning rules. We review the Content Addressable Network (CAN) learning algorithm, a discrete learning algorithm that provides accelerated learning with reduced hardware requirements. We then show how the CAN algorithm can be effectively mapped onto D-STOP, and we investigate associated optoelectronic hardware tradeoffs.",
author = "Krishnamoorthy, {Ashok V.} and Brodsky, {Stephen A.} and Guest, {Clark C.} and Marsden, {Gary C.} and Matthias Blume and Gokce Yayla and Jean Merckle and Sadik Esener",
year = "1994",
language = "English (US)",
volume = "3",
pages = "1998--2003",
booktitle = "IEEE International Conference on Neural Networks - Conference Proceedings",
publisher = "IEEE",

}

TY - GEN

T1 - Hardware efficient learning on a 3-D optoelectronic neural system

AU - Krishnamoorthy, Ashok V.

AU - Brodsky, Stephen A.

AU - Guest, Clark C.

AU - Marsden, Gary C.

AU - Blume, Matthias

AU - Yayla, Gokce

AU - Merckle, Jean

AU - Esener, Sadik

PY - 1994

Y1 - 1994

N2 - We discuss the Dual-Scale Topology Optoelectronic Processor (D-STOP) neural network, a scalable, optically interconnected neural network architecture. We present the tandem D-STOP system, which provides the connectivity needed for building fully-parallel neural networks with generic gradient-descent learning rules. We review the Content Addressable Network (CAN) learning algorithm, a discrete learning algorithm that provides accelerated learning with reduced hardware requirements. We then show how the CAN algorithm can be effectively mapped onto D-STOP, and we investigate associated optoelectronic hardware tradeoffs.

AB - We discuss the Dual-Scale Topology Optoelectronic Processor (D-STOP) neural network, a scalable, optically interconnected neural network architecture. We present the tandem D-STOP system, which provides the connectivity needed for building fully-parallel neural networks with generic gradient-descent learning rules. We review the Content Addressable Network (CAN) learning algorithm, a discrete learning algorithm that provides accelerated learning with reduced hardware requirements. We then show how the CAN algorithm can be effectively mapped onto D-STOP, and we investigate associated optoelectronic hardware tradeoffs.

UR - http://www.scopus.com/inward/record.url?scp=0028752593&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0028752593&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0028752593

VL - 3

SP - 1998

EP - 2003

BT - IEEE International Conference on Neural Networks - Conference Proceedings

PB - IEEE

ER -