Dense Matrix Multiplication Algorithms and Performance Evaluation of HPCC in 81 Nodes IBM Power 8 Architecture

UDC.coleccionInvestigaciónes_ES
UDC.departamentoFísica e Ciencias da Terraes_ES
UDC.endPage20es_ES
UDC.grupoInvGrupo de Polímeroses_ES
UDC.issue8es_ES
UDC.journalTitleComputationes_ES
UDC.startPage1es_ES
UDC.volume9es_ES
dc.contributor.authorEstévez Ruiz, Eduardo Patricio
dc.contributor.authorCaluña, Giovanny
dc.contributor.authorJiménez Patiño, Fabian Rodolfo
dc.contributor.authorLópez, Joaquín
dc.contributor.authorThirumuruganandham, Saravana Prakash
dc.date.accessioned2021-11-11T13:27:10Z
dc.date.available2021-11-11T13:27:10Z
dc.date.issued2021-08
dc.description.abstract[Abstract] Optimizing HPC systems based on performance factors and bottlenecks is essential for designing an HPC infrastructure with the best characteristics and at a reasonable cost. Such insight can only be achieved through a detailed analysis of existing HPC systems and the execution of their workloads. The “Quinde I” is the only and most powerful supercomputer in Ecuador and is currently listed third on the South America. It was built with the IBM Power 8 servers. In this work, we measured its performance using different parameters from High-Performance Computing (HPC) to compare it with theoretical values and values obtained from tests on similar models. To measure its performance, we compiled and ran different benchmarks with the specific optimization flags for Power 8 to get the maximum performance with the current configuration in the hardware installed by the vendor. The inputs of the benchmarks were varied to analyze their impact on the system performance. In addition, we compile and compare the performance of two algorithms for dense matrix multiplication SRUMMA and DGEMM.es_ES
dc.description.sponsorshipThis research was funded by the seed grant “Computational modelling of biomaterials and applications to bioengineering and infectious disease, Universidad Technologica Indoamérica, Ecuador” awarded to S.P.T.
dc.identifier.citationEstévez Ruiz, E.P.; Chicaiza, G.E.C.; Patiño, F.R.J.; López Lago, J.C.; Thirumuruganandham, S.P. Dense Matrix Multiplication Algorithms and Performance Evaluation of HPCC in 81 Nodes IBM Power 8 Architecture. Computation 2021, 9, 86. https://doi.org/10.3390/computation9080086es_ES
dc.identifier.doi10.3390/computation9080086
dc.identifier.issn2079-3197
dc.identifier.urihttp://hdl.handle.net/2183/28859
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relation.urihttps://doi.org/10.3390/computation9080086es_ES
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)es_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectSupercomputeres_ES
dc.subjectPerformancees_ES
dc.subjectBenchmarkes_ES
dc.subjectIBM Power 8es_ES
dc.subjectHPCes_ES
dc.subjectClusteres_ES
dc.subjectDGEMMes_ES
dc.subjectSRUMMAes_ES
dc.subjectParallel computinges_ES
dc.titleDense Matrix Multiplication Algorithms and Performance Evaluation of HPCC in 81 Nodes IBM Power 8 Architecturees_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublication80f07055-ad4b-45b5-806a-b59dda8b3209
relation.isAuthorOfPublication.latestForDiscovery80f07055-ad4b-45b5-806a-b59dda8b3209

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