Title :
Optimal task clustering using Hopfield net
Author :
Zhu, Weiping ; Liang, Tyng-Yeu ; Shieh, Ce-Kuen
Author_Institution :
Sch. of Inf. Technol., Queensland Univ., Qld., Australia
Abstract :
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
Keywords :
Hopfield neural nets; distributed memory systems; shared memory systems; Hopfield neural network; distributed system; load balancing; load communication; optimal task clustering; static method; Clustering methods; Computer architecture; Cost function; Electronic mail; Hopfield neural networks; Information technology; Load management; Neural networks; Neurons; System testing;
Conference_Titel :
Algorithms and Architectures for Parallel Processing, 1997. ICAPP 97., 1997 3rd International Conference on
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-4229-1
DOI :
10.1109/ICAPP.1997.651513
