Scheduling strategies for mapping application workflows onto the grid
In this work, we describe new strategies for scheduling and executing workflow applications on grid resources using the GrADS [Ken Kennedy et al., 2002] infrastructure. Workflow scheduling is based on heuristic scheduling strategies that use application component performance models. The workflow is...
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| Veröffentlicht in: | 2005 14th IEEE International Symposium on High Performance Distributed Computing S. 125 - 134 |
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| Sprache: | Englisch |
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2005
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| ISBN: | 9780780390379, 0780390377 |
| ISSN: | 1082-8907 |
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| Abstract | In this work, we describe new strategies for scheduling and executing workflow applications on grid resources using the GrADS [Ken Kennedy et al., 2002] infrastructure. Workflow scheduling is based on heuristic scheduling strategies that use application component performance models. The workflow is executed using a novel strategy to bind and launch the application onto heterogeneous resources. We apply these strategies in the context of executing EMAN, a bio-imaging workflow application, on the grid. The results of our experiments show that our strategy of performance model based, in-advance heuristic workflow scheduling results in 1.5 to 2.2 times better makespan than other existing scheduling strategies. This strategy also achieves optimal load balance across the different grid sites for this application. |
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| AbstractList | In this work, we describe new strategies for scheduling and executing workflow applications on grid resources using the GrADS [Ken Kennedy et al., 2002] infrastructure. Workflow scheduling is based on heuristic scheduling strategies that use application component performance models. The workflow is executed using a novel strategy to bind and launch the application onto heterogeneous resources. We apply these strategies in the context of executing EMAN, a bio-imaging workflow application, on the grid. The results of our experiments show that our strategy of performance model based, in-advance heuristic workflow scheduling results in 1.5 to 2.2 times better makespan than other existing scheduling strategies. This strategy also achieves optimal load balance across the different grid sites for this application. |
| Author | Mellor-Crummey, J. Johnsson, L. Marin, G. Liu, B. Koelbel, C. Anirban Mandal Kennedy, K. |
| Author_xml | – sequence: 1 surname: Anirban Mandal fullname: Anirban Mandal organization: Dept. of Comput. Sci., Rice Univ., Houston, TX, USA – sequence: 2 givenname: K. surname: Kennedy fullname: Kennedy, K. organization: Dept. of Comput. Sci., Rice Univ., Houston, TX, USA – sequence: 3 givenname: C. surname: Koelbel fullname: Koelbel, C. organization: Dept. of Comput. Sci., Rice Univ., Houston, TX, USA – sequence: 4 givenname: G. surname: Marin fullname: Marin, G. organization: Dept. of Comput. Sci., Rice Univ., Houston, TX, USA – sequence: 5 givenname: J. surname: Mellor-Crummey fullname: Mellor-Crummey, J. organization: Dept. of Comput. Sci., Rice Univ., Houston, TX, USA – sequence: 6 givenname: B. surname: Liu fullname: Liu, B. – sequence: 7 givenname: L. surname: Johnsson fullname: Johnsson, L. |
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| Title | Scheduling strategies for mapping application workflows onto the grid |
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