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a hierarchical and distributed approach for mapping large applications to heterogeneous grids using genetic algorithmsIn 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.
Document ID
20040010817
Document Type
Preprint (Draft being sent to journal)
Authors
Sanyal, Soumya
(Texas Univ. Arlington, TX, United States)
Jain, Amit
(Texas Univ. Arlington, TX, United States)
Das, Sajal K.
(Texas Univ. Arlington, TX, United States)
Biswas, Rupak
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 21, 2013
Publication Date
November 1, 2003
Subject Category
Computer Systems
Meeting Information
IEEE 5th International Conference on Cluster Computing(Hong Kong)
Funding Number(s)
WBS: WBS 302-15-41
CONTRACT_GRANT: NCC2-5395
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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