On construction of a well-balanced allocation strategy for heterogeneous multi-cluster computing environments
With the rapid increment of the heterogeneity of hardware devices, cluster computing has to encounter the problem of handling heterogeneous resources for exploiting the utilization of system resources. This paper introduces a new job allocation strategy based on multi-clusters in diskless environmen...
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Published in | The Journal of supercomputing Vol. 56; no. 3; pp. 270 - 299 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Boston
Springer US
01.06.2011
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ISSN | 0920-8542 1573-0484 |
DOI | 10.1007/s11227-009-0369-3 |
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Abstract | With the rapid increment of the heterogeneity of hardware devices, cluster computing has to encounter the problem of handling heterogeneous resources for exploiting the utilization of system resources. This paper introduces a new job allocation strategy based on multi-clusters in diskless environments. By adopting Ganglia as the resource monitor and Condor as the queue system, a heterogeneous multi-cluster system is also constructed with and without storage devices for evaluating the system performance. The proposed algorithm is called the Well-Balanced Allocation Strategy (WBAS) in which the scheduler dispatches MPI-based jobs to appropriate resources across multi-clusters. The strategy focuses on dispatching jobs to nodes with similar performance, thus equalizing execution times among all the required nodes. The WBAS is implemented on the constructed heterogeneous multi-cluster system to evaluate the performance of the scheduling strategy. The experimental results show that the proposed strategy performs well and could efficiently improve the system performance. |
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AbstractList | With the rapid increment of the heterogeneity of hardware devices, cluster computing has to encounter the problem of handling heterogeneous resources for exploiting the utilization of system resources. This paper introduces a new job allocation strategy based on multi-clusters in diskless environments. By adopting Ganglia as the resource monitor and Condor as the queue system, a heterogeneous multi-cluster system is also constructed with and without storage devices for evaluating the system performance. The proposed algorithm is called the Well-Balanced Allocation Strategy (WBAS) in which the scheduler dispatches MPI-based jobs to appropriate resources across multi-clusters. The strategy focuses on dispatching jobs to nodes with similar performance, thus equalizing execution times among all the required nodes. The WBAS is implemented on the constructed heterogeneous multi-cluster system to evaluate the performance of the scheduling strategy. The experimental results show that the proposed strategy performs well and could efficiently improve the system performance. |
Author | Tung, Hao-Yu Lai, Kuan-Chou Yang, Chao-Tung |
Author_xml | – sequence: 1 givenname: Chao-Tung surname: Yang fullname: Yang, Chao-Tung email: ctyang@thu.edu.tw organization: High-Performance Computing Laboratory, Department of Computer Science, Tunghai University – sequence: 2 givenname: Kuan-Chou surname: Lai fullname: Lai, Kuan-Chou organization: Department of Computer and Information Science, National Taichung University – sequence: 3 givenname: Hao-Yu surname: Tung fullname: Tung, Hao-Yu organization: High-Performance Computing Laboratory, Department of Computer Science, Tunghai University |
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Cites_doi | 10.1007/s10586-006-9747-2 10.1142/S0218001495000110 10.1109/40.342018 10.1016/j.future.2006.04.007 10.1109/TPDS.2007.1036 10.1111/j.1467-8659.1987.tb00340.x 10.1007/s11227-005-2337-x 10.1007/s11227-006-8300-7 10.1006/jpdc.1995.1011 10.1109/PDCAT.2006.8 10.1109/PDCAT.2006.77 10.1109/GCC.2006.10 10.1109/HPDC.2006.1652160 10.1109/FGCN.2007.9 10.1177/109434200101500302 10.1109/CCGRID.2003.1199347 |
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SubjectTerms | Algorithms Allocations Compilers Computation Computer Science Construction Devices Heterogeneity Interpreters Performance evaluation Processor Architectures Programming Languages Strategy |
Title | On construction of a well-balanced allocation strategy for heterogeneous multi-cluster computing environments |
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