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Improving Many-Task Computing in Scientific Workflows Using P2P Techniques
Abstract : Large-scale scientific experiments are usually supported by scientific workflows that may demand high performance computing infrastructure. Within a given experiment, the same workflow may be explored with different sets of parameters. However, the parallelization of the workflow instances is hard to be accomplished mainly due to the heterogeneity of its activities. Many-Task computing paradigm seems to be a candidate approach to support workflow activity parallelism. However, scheduling a huge amount of workflow activities on large clusters may be susceptible to resource failures and overloading. In this paper, we propose Heracles, an approach to apply consolidated P2P techniques to improve Many-Task computing of workflow activities on large clusters. We present a fault tolerance mechanism, a dynamic resource management and a hierarchical organization of computing nodes to handle workflow instances execution properly. We have evaluated Heracles by executing experimental analysis regarding the benefits of P2P techniques on the workflow execution time.
Cited literature [30 references]
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00641008
Contributor : Fady Draidi <>
Submitted on : Monday, November 14, 2011 - 4:04:57 PM
Last modification on : Tuesday, December 4, 2018 - 2:32:05 PM
Document(s) archivé(s) le : Wednesday, February 15, 2012 - 2:27:11 AM
Contributor : Fady Draidi <>
Submitted on : Monday, November 14, 2011 - 4:04:57 PM
Last modification on : Tuesday, December 4, 2018 - 2:32:05 PM
Document(s) archivé(s) le : Wednesday, February 15, 2012 - 2:27:11 AM
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paper07-1.pdf
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