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Conference Papers Year : 2006

Probabilistic and dynamic optimization of job partitioning on a grid infrastructure

Abstract

Production grids have a potential for parallel execution of a very large number of tasks but also introduce a high overhead that significantly impacts the execution of short tasks. In this work, we present a strategy to optimize the partitioning of jobs on a grid infrastructure. This method takes into account the variability and the difficulty to model a multi-user large-scale environment used for production. It is based on probabilistic estimations of the grid overhead. We first study analytically modeled environments and then we show results on a real grid infrastructure. We demonstrate that this method leads to a significant time speed-up and to a substantial saving of the number of submitted tasks with respect to a blind maximal partitioning strategy.
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Dates and versions

hal-00683203 , version 1 (28-03-2012)

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Tristan Glatard, Johan Montagnat, Xavier Pennec. Probabilistic and dynamic optimization of job partitioning on a grid infrastructure. Parallel, Distributed and network-based Processing, Feb 2006, Montbéliard-Sochaux, France. pp.231-238, ⟨10.1109/PDP.2006.61⟩. ⟨hal-00683203⟩
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