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Los Angeles, CA
March 31, 2009 to April 2, 2009
ISBN: 978-0-7695-3507-4
pp: 466-470
ABSTRACT
This paper presents alternatives and performance results obtained by analyzing parallelization on a cluster of multicore nodes. The ultimate goal is to show if both shared and distributed memory parallel processing models need to be taken into account independently, or if one affects the other and both must be considered simultaneosly. The application used as a testbed is classical in the context of high performance computing: matrix multiplication. Results are shown in terms of the conditions under which performance is optimized and where to focus the parallelization efforts on clusters with nodes with multiple cores, based on experiments combining both kinds of parallel models. In any case, all processing units should be effectively used in order to optimize the performance of parallel applications.
INDEX TERMS
Parallel Computing, Cluster of Multicore Nodes, Shared and Distributed Memory Parellel Models, Parallelization performance
CITATION
Fernando G. Tinetti, Gustavo Wolfmann, "Parallelization Analysis on Clusters of Multicore Nodes Using Shared and Distributed Memory Parallel Computing Models", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 466-470, doi:10.1109/CSIE.2009.185
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