Neural network routing for multiple stage interconnection networks

Mark W. Goudreau, C. Lee Giles

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

Abstract

Summary form only given, a follows. A Hopfield model neural network can be useful as a form of parallel computer. Such a neural network may be capable of arriving at a problem solution with much more speed than conventional, sequential approaches. This concept has been applied to the problem of generating control bits for a multistage interconnection network. A Hopfield model neural network has been designed that is capable of routing a set of messages. This neural network solution is especially useful for interconnection networks that are not self-routing and interconnection networks that have an irregular structure. Furthermore, the neural network routing scheme is fault-tolerant. Results were obtained on generating routes in a 4 × 4 Benes interconnection network.

Original languageEnglish (US)
Title of host publicationProceedings. IJCNN - International Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Number of pages1
ISBN (Print)0780301641
StatePublished - Jan 1 1992
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: Jul 8 1991Jul 12 1991

Publication series

NameProceedings. IJCNN - International Joint Conference on Neural Networks

Other

OtherInternational Joint Conference on Neural Networks - IJCNN-91-Seattle
CitySeattle, WA, USA
Period7/8/917/12/91

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Goudreau, M. W., & Giles, C. L. (1992). Neural network routing for multiple stage interconnection networks. In Anon (Ed.), Proceedings. IJCNN - International Joint Conference on Neural Networks (Proceedings. IJCNN - International Joint Conference on Neural Networks). Publ by IEEE.