Anand, Sunil Kumar and Srikant, YN (2005) Genetic Algorithm based Automatic Data Partitioning Scheme for HPF. In: 14th IEEE International Symposium on High Performance Distributed Computing, HPDC-14, 24-27 July 2005, Research Triangle Park, North Carolina, USA, pp. 289-290.
The performance of a parallel program depends largely on its data partitions.So a good data partitioning scheme is the need of the time. However it is very difficult to arrive at a good solution as the number of possible data partitions for a given real life program is exponential in the size of the program. We present a heuristic technique for automatic data partitioning for HPF. Our approach is based on Genetic Algorithms and is very simple, yet very efficient to quickly find appropriate data partitions even for large programs with large number of alternatives for data distribution.It makes use of both static as well as dynamic data distribution with the main aim of reducing the overall execution time of the entire program.
|Item Type:||Conference Paper|
|Additional Information:||©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Department/Centre:||Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)|
|Date Deposited:||06 Feb 2008|
|Last Modified:||19 Sep 2010 04:42|
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