Neural-network-based multistage interconnection network routing

Venkatnarayan Krishnamoorthy; Yi Pan; Yanqing Zhang

doi:10.1117/12.485695

4 August 2003 Neural-network-based multistage interconnection network routing

Venkatnarayan Krishnamoorthy, Yi Pan, Yanqing Zhang

Proceedings Volume 5103, Intelligent Computing: Theory and Applications; (2003) https://doi.org/10.1117/12.485695
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Techniques based on neural networks can provide efficient solutions to a wide variety of problems in computer science. Routing in computer networks is to schedule messages and select communication links so that messages can be transferred efficiently between source and destination processors. Finding an optimal solution to many routing problems usually reqrueis exponential time and is impractical in reality. Hence, many heuristic algorithms have been designed to find sub-optimal solutions. In this research we use neural networks with a set of constraints to capture various collisions in multistage interconnection networks (MINs). Our simulation results have indicated that the Hopfield neural network can be used to routing to avoid link collisions in electronic MINs and crosstalks in optical MINs.

Citation Download Citation

Venkatnarayan Krishnamoorthy, Yi Pan, and Yanqing Zhang "Neural-network-based multistage interconnection network routing", Proc. SPIE 5103, Intelligent Computing: Theory and Applications, (4 August 2003); https://doi.org/10.1117/12.485695

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