Patnaik, LM and Udaykumar, S (1999) Mapping adaptive resonance theory onto ring and mesh architectures. In: Neurocomputing, 25 (1-3). 39-54 .
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In recent years, parallel computers have been attracting attention for simulating artificial neural networks (ANN). This is due to the inherent parallelism in ANN. This work is aimed at studying ways of parallelizing adaptive resonance theory (ART), a popular neural network algorithm. The core computations of ART are separated and different strategies of parallelizing ART are discussed. We present mapping strategies for ART 2-A neural network onto ring and mesh architectures. The required parallel architecture is simulated using a parallel architectural simulator, PROTEUS and parallel programs are written using a superset of C for the algorithms presented. A simulation-based scalability study of the algorithm-architecture match is carried out. The various overheads are identified in order to suggest ways of improving the performance. Our main objective is to find out the performance of the ART2-A network on different parallel architectures. (C) 1999 Elsevier Science B.V. All rights reserved.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Elsevier Science.|
|Keywords:||Arti"cial neural networks;Adaptive resonance theory;Parallel architectures;Ring and mesh architectures|
|Date Deposited:||30 Jun 2011 11:48|
|Last Modified:||30 Jun 2011 11:48|
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