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Load sharing in the training set partition algorithm for parallel neural learning

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2 Author(s)
B. Girau ; Lab. d'Inf. du Parallelisme, CNRS, Lyon, France ; H. Paugam-Moisy

A parallel back-propagation algorithm that partitions the training set on a ring of processors has been introduced. In this paper, we study the performance of this algorithm on MIMD machines and develop a new version, based on a heterogeneous load sharing. Algebraic models allow precise comparisons between the different methods, and show great improvements in case of parallel learning

Published in:

Parallel Processing Symposium, 1995. Proceedings., 9th International

Date of Conference:

25-28 Apr 1995