Discovering the Structure of a Self-Routing Interconnection Network with a Recurrent Neural Network1

Mark W. Goudreau* and C. Lee Giles

NEC Research Institute4 Independence Way, Princeton, NJ 08540giles@research.nj.nec.com*currently at Dept. of Computer ScienceU. of Central Florida, Orlando, FL 32816goudreau@cs.ucf.edu

Abstract

A Recurrent Neural Network (RNN) is used to learn the structure of an Interconnection Network (IN) by training with examples of routing messages. This is essentially the same as using RNNs to learn the structure of a synchronous sequential machine for which there are many distinct initial states. The method is illustrated by learning a small Self-Routing Interconnection Network (SRIN) with 6 switches by training a second ...

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