Comparison of Performance Analysis Tools for Parallel Programs Applied to CombBLAS

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dc.contributor.advisorGobbert, Matthias K.
dc.contributor.authorCollins, Wesley
dc.contributor.authorMartinez, Daniel T.
dc.contributor.authorMonaghan, Michael
dc.contributor.authorMunishkin, Alexey A.
dc.contributor.authorBlenkhorn, Ari Rapkin
dc.contributor.authorGraf, Jonathan S.
dc.contributor.authorKhuvis, Samuel
dc.contributor.authorLinford, John C.
dc.date.accessioned2018-10-11T13:28:43Z
dc.date.available2018-10-11T13:28:43Z
dc.date.issued2015
dc.description.abstractPerformance analysis tools are powerful tools for high performance computing. By breaking down a program into how long the CPUs are taking on each process (pro- filing) or showing when events take place on a timeline over the course of running a program (tracing), a performance analysis tool can tell the programmer exactly, where the computer is running slowly. With this information, the programmer can focus on these performance "hotspots," and the code can be optimized to run faster. We com- pared the performance analysis tools TAU, ParaTools ThreadSpotter, Intel VTune, Scalasca, HPCToolkit, and Score-P to the example code CombBLAS (combinatorial BLAS) which is a C++ implemenation of the GraphBLAS, a set of graph algorithms using BLAS (Basic Linear Algebra Subroutines). Using these performance analysis tools on CombBLAS, we found three major "hotspots" and attempted to improve the code. We were unsuccessful in improving these "hotspots" due to a time limitation but still gave suggestions on improving the OpenMP calls in the CombBLAS code.en_US
dc.description.urihttps://userpages.umbc.edu/~gobbert/papers/REU2015Team8.pdfen_US
dc.format.extent22 pagesen_US
dc.genreTechnical Reporten_US
dc.identifierdoi:10.13016/M23F4KR7V
dc.identifier.urihttp://hdl.handle.net/11603/11468
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Mathematics and Statistics Department
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Mathematics and Statistics Department
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofseriesHPCF Technical Report;HPCF-2015-28
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.subjectTAUen_US
dc.subjectThreadSpotteren_US
dc.subjectIntel VTuneen_US
dc.subjectScalascaen_US
dc.subjectHPCToolkiten_US
dc.subjectScore-Pen_US
dc.subjectUMBC High Performance Computing Facility (HPCF)en_US
dc.titleComparison of Performance Analysis Tools for Parallel Programs Applied to CombBLASen_US
dc.typeTexten_US

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