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Methodology for efficient Execution of SPMD applications on Multicore Clusters
Keywords:
high performance computingAbstract
Nowadays, the scientific applications are developed with more complexity and accuracy and these precisions need high computational resources to be executed. Also, the current trend in high performance computing (HPC) is to find clusters composed of Multicore nodes, and these nodes include heterogeneity levels which have to be handled carefully if we want to improve the performance metrics. The integration of these Multicore nodes in HPC (High Performance Computing) has allowed the inclusion of more parallelism within nodes, but this parallelism generates challenges that have to be managed considering some troubles present in these environments that affect the application efficiency and speedup. Aspects associated to number of cores, data locality, shared cache, communications link inside the node, etc are considered relevant when our goal is to improve the performance.
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References
[1] M. McCool. Scalable programming models for massively multicore processors. Proc of the IEEE, pages 816-831, (2008).
[2] G. Mercier and J. Clet-Ortega. Towards an efficient process placement policy for mpi applications in multicore environments. Euro PVM/MPI, Lecture Notes in Computer Science Springer, 5759/2009:104{115, (2009).
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[4] R. Muresano, D. Rexachs, E. luque., How SPMD applications could be efficiently executed on multicore environment, IEEE International Conference on Cluster Computing (Cluster 2009).
[5] R. Muresano, D. Rexachs, and E. Luque. Methodology for efficient execution of spmd applications on multicore clusters. 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGRID), IEEE Computer Society, pages 185-195, (2010).
[6] R. Muresano, D. Rexachs, and E. Luque. A tool for efficient execution of spmd applications on multicore clusters. International Conference on Computational Science, ICCS 2010, Procedia Computer Science, 1:2593{2602, (2010)
[7] R. Muresano, D. Rexachs, and E. Luque. Combining Scalability and Efficiency for SPMD Applications on Multicore Clusters, The 2011 International Conference on Parallel and Distributed Processing Techniques and Application PDPTA 2011, pages XX-XXX (2011)
[2] G. Mercier and J. Clet-Ortega. Towards an efficient process placement policy for mpi applications in multicore environments. Euro PVM/MPI, Lecture Notes in Computer Science Springer, 5759/2009:104{115, (2009).
[3] L. M. Liebrock and S. P. Goudy, “Methodology for modeling spmd hybrid parallel computation,” Concurr. Comput. : Pract. Exper., vol. 20, no. 8, pp. 903–940, 2008.
[4] R. Muresano, D. Rexachs, E. luque., How SPMD applications could be efficiently executed on multicore environment, IEEE International Conference on Cluster Computing (Cluster 2009).
[5] R. Muresano, D. Rexachs, and E. Luque. Methodology for efficient execution of spmd applications on multicore clusters. 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGRID), IEEE Computer Society, pages 185-195, (2010).
[6] R. Muresano, D. Rexachs, and E. Luque. A tool for efficient execution of spmd applications on multicore clusters. International Conference on Computational Science, ICCS 2010, Procedia Computer Science, 1:2593{2602, (2010)
[7] R. Muresano, D. Rexachs, and E. Luque. Combining Scalability and Efficiency for SPMD Applications on Multicore Clusters, The 2011 International Conference on Parallel and Distributed Processing Techniques and Application PDPTA 2011, pages XX-XXX (2011)
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Published
2011-10-03
How to Cite
Muresano, R. (2011). Methodology for efficient Execution of SPMD applications on Multicore Clusters. Journal of Computer Science and Technology, 11(02), p. 111–112. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/677
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