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Optimal task clustering using Hopfield net

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3 Author(s)
Zhu, Weiping ; Sch. of Inf. Technol., Queensland Univ., Qld., Australia ; Tyng-Yeu Liang ; Ce-Kuen Shieh

To achieve high performance in a distributed system, the tasks of a program have to be carefully clustered and assigned to processors. In this paper we present a static method to cluster tasks and allocate them to processors. The proposed method relies on the Hopfield neural network to achieve optimum or near-optimum task clustering in terms of load balancing and communication cost. Experimental studies show that this method indeed can find optimal or near-optimal mapping for those programs used in our tests

Published in:

Algorithms and Architectures for Parallel Processing, 1997. ICAPP 97., 1997 3rd International Conference on

Date of Conference:

10-12 Dec 1997