MVAPICH2 vs. OpenMPI for a Clustering Algorithm

dc.contributor.authorBlasberg, Robin V.
dc.contributor.authorGobbert, Matthias K.
dc.date.accessioned2018-10-24T18:39:34Z
dc.date.available2018-10-24T18:39:34Z
dc.date.issued2008
dc.description.abstractAffinity propagation is a clustering algorithm that functions by identifying similar data points in an iterative process. Its structure allows for taking full advantage of parallel computing to enable the solution of larger problems and to solve them faster than possible in serial. We present a memory-optimal implementation with minimal number of communication commands and demonstrate its excellent scalability. Additionally, we present a comparison of two implementations of MPI that demonstrate that MVAPICH2 exhibits better scalability up to larger numbers of parallel processes than OpenMPI for this code.en_US
dc.description.urihttps://userpages.umbc.edu/~gobbert/papers/BlasbergGobbertHPCF20087.pdfen_US
dc.format.extent12 pagesen_US
dc.genretechnical reporten_US
dc.identifierdoi:10.13016/M2ZG6GB54
dc.identifier.urihttp://hdl.handle.net/11603/11673
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Mathematics Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofseriesHPCF Technical Report;HPCF-2008-7
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectOpenMPIen_US
dc.subjectClustering Algorithmen_US
dc.subjectMVAPICH2en_US
dc.subjectmemory-optimalen_US
dc.subjectUMBC High Performance Computing Facility (HPCF)en_US
dc.subjectaffinity propogation
dc.titleMVAPICH2 vs. OpenMPI for a Clustering Algorithmen_US
dc.typeTexten_US

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