Multiple job co-allocation strategy for heterogeneous multi-cluster systems based on linear programming
Multi-cluster environments are composed of multiple clusters of computers that act collaboratively, and thus allowing computational problems to be treated that require more resources than those available in a single cluster. However, the degree of complexity of the scheduling process is greatly incr...
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Published in | Journal of supercomputing Vol. 58; no. 3; pp. 394 - 402 |
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Main Authors | , , , |
Format | Journal Article Conference Proceeding |
Language | English |
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Springer US
01.12.2011
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Abstract | Multi-cluster environments are composed of multiple clusters of computers that act collaboratively, and thus allowing computational problems to be treated that require more resources than those available in a single cluster. However, the degree of complexity of the scheduling process is greatly increased by the heterogeneity of resources and co-allocation process, which distributes the tasks of parallel jobs across cluster boundaries.
This work presents a new scheduling strategy that allocates multiple jobs from the system queue simultaneously on a heterogeneous multicluster, by applying co-allocation when is necessary. Our strategy is composed by a job selection function and a linear programming model to find the best allocation for multiple jobs. The proposed scheduling technique is shown to reduce the execution times of the parallel jobs and the overall response times by 38% compared with other scheduling techniques in the literature. |
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AbstractList | Multi-cluster environments are composed of multiple clusters of computers that act collaboratively, and thus allowing computational problems to be treated that require more resources than those available in a single cluster. However, the degree of complexity of the scheduling process is greatly increased by the heterogeneity of resources and co-allocation process, which distributes the tasks of parallel jobs across cluster boundaries.
This work presents a new scheduling strategy that allocates multiple jobs from the system queue simultaneously on a heterogeneous multicluster, by applying co-allocation when is necessary. Our strategy is composed by a job selection function and a linear programming model to find the best allocation for multiple jobs. The proposed scheduling technique is shown to reduce the execution times of the parallel jobs and the overall response times by 38% compared with other scheduling techniques in the literature. |
Author | Cores, Fernando Blanco, Héctor Guirado, Fernando Lérida, Josep Lluís |
Author_xml | – sequence: 1 givenname: Héctor surname: Blanco fullname: Blanco, Héctor email: hectorblanco@diei.udl.cat organization: Department of Computer Science, Universitat de Lleida – sequence: 2 givenname: Josep Lluís surname: Lérida fullname: Lérida, Josep Lluís organization: Department of Computer Science, Universitat de Lleida – sequence: 3 givenname: Fernando surname: Cores fullname: Cores, Fernando organization: Department of Computer Science, Universitat de Lleida – sequence: 4 givenname: Fernando surname: Guirado fullname: Guirado, Fernando organization: Department of Computer Science, Universitat de Lleida |
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Cites_doi | 10.1016/j.parco.2006.09.006 10.1109/TPDS.2007.1036 10.1006/jpdc.2000.1714 10.1007/s11227-005-2337-x 10.1109/CLUSTR.2003.1253294 |
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Keywords | Multi-cluster systems Mixed integer programming Co-allocation Job scheduling Resource allocation Task scheduling Calculator cluster Linear programming Scheduling Distributed system Distributed computing Selection function Time response Linear model Workload Heterogeneity Response time Parallelism Queue Execution time |
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Title | Multiple job co-allocation strategy for heterogeneous multi-cluster systems based on linear programming |
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