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Fifth IEEE International Conference on Cluster Computing (CLUSTER'03)
A Hierarchical and Distributed Approach for Mapping Large Applications to Heterogeneous Grids Using Genetic Algorithms
Hong Kong
December 01-December 04
ISBN: 0-7695-2066-9
Soumya Sanyal, University of Texas at Arlington
Amit Jain, University of Texas at Arlington
Sajal K. Das, University of Texas at Arlington
Rupak Biswas, NASA Ames Research Center
In this paper, we propose a distributed approach for mapping a single large application to a heterogeneous grid environment. To minimize the execution time of the parallel application, we distribute the mapping overhead to the available nodes of the grid. This approach not only provides a fast mapping of tasks to resources but is also scalable. We adopt a hierarchical grid model and accomplish the job of mapping tasks to this topology using a scheduler tree. Results show that our three-phase algorithm provides high quality mappings, and is fast and scalable.
Citation:
Soumya Sanyal, Amit Jain, Sajal K. Das, Rupak Biswas, "A Hierarchical and Distributed Approach for Mapping Large Applications to Heterogeneous Grids Using Genetic Algorithms," cluster, pp.496, Fifth IEEE International Conference on Cluster Computing (CLUSTER'03), 2003
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