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A hypergraph partitioning based approach for scheduling of tasks with batch-shared I/O

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7 Author(s)
Gaurav Khanna ; Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA ; Nagavijayalakshmi Vydyanathan ; Kurc, T. ; Catalyurek, U.
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This paper proposes a novel, hypergraph partitioning based strategy to schedule multiple data analysis tasks with batch-shared I/O behavior. This strategy formulates the sharing of files among tasks as a hypergraph to minimize the I/O overheads due to transferring of the same set of files multiple times and employs a dynamic scheme for file transfers to reduce contention on the storage system. We experimentally evaluate the proposed approach using application emulators from two application domains; analysis of remotely-sensed data and biomedical imaging.

Published in:

Cluster Computing and the Grid, 2005. CCGrid 2005. IEEE International Symposium on  (Volume:2 )

Date of Conference:

9-12 May 2005