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A hierarchical and distributed approach for mapping large applications to heterogeneous grids using genetic algorithms

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4 Author(s)
Sanyal, S. ; Dept. of Comput. Sci. & Eng., Texas Univ. at Arlington, TX, USA ; Amit Jain ; Das, S.K. ; Biswas, R.

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.

Published in:

Cluster Computing, 2003. Proceedings. 2003 IEEE International Conference on

Date of Conference:

1-4 Dec. 2003

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