16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008) Comparison of Batch Scheduling for Identical Multi-Tasks Jobs on Heterogeneous Platforms February 13-February 15 ISBN: 978-0-7695-3089-5
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PDP.2008.50
In this paper we consider the scheduling of a batch of the same job on a heterogeneous execution platform. A job is represented by a directed acyclic graph without forks (intree) but with typed tasks. The execution resources are distributed and each resource can carry out a set of task types. The objective function is to minimize the makespan of the batch execution. Three algorithms are studied in this context: an on-line algorithm, a genetic algorithm and a steady-state algorithm. The contribution of this paper is on the experimental analysis of these algorithms and on their adaptation to the context. We show that their performances depend on the size of the batch and on the characteristics of the execution platform.
Index Terms:
Batch scheduling, grid computing, heterogeneous platform, on-line scheduling, steady state scheduling, genetic algorithm
Citation:
Sekou Diakite, Jean-Marc Nicod, Laurent Philippe, "Comparison of Batch Scheduling for Identical Multi-Tasks Jobs on Heterogeneous Platforms," pdp, pp.374-378, 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008), 2008 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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