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Programming parallel dense matrix factorizations with look-ahead and OpenMP

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Programming parallel dense matrix factorizations with look-ahead and OpenMP

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dc.contributor.author Catalán, Sandra es_ES
dc.contributor.author Castelló, Adrián es_ES
dc.contributor.author Igual, Francisco D. es_ES
dc.contributor.author Rodríguez-Sánchez, Rafael es_ES
dc.contributor.author Quintana Ortí, Enrique Salvador es_ES
dc.date.accessioned 2021-05-14T03:31:47Z
dc.date.available 2021-05-14T03:31:47Z
dc.date.issued 2020-03 es_ES
dc.identifier.issn 1386-7857 es_ES
dc.identifier.uri http://hdl.handle.net/10251/166343
dc.description.abstract [EN] We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using OpenMP, that departs from the legacy (or conventional) solution, which simply extracts concurrency from a multi-threaded version of basic linear algebra subroutines (BLAS). The proposed approach is also different from the more sophisticated runtime-based implementations, which decompose the operation into tasks and identify dependencies via directives and runtime support. Instead, our strategy attains high performance by explicitly embedding a static look-ahead technique into the DMF code, in order to overcome the performance bottleneck of the panel factorization, and realizing the trailing update via a cache-aware multi-threaded implementation of the BLAS. Although the parallel algorithms are specified with a high level of abstraction, the actual implementation can be easily derived from them, paving the road to deriving a high performance implementation of a considerable fraction of linear algebra package (LAPACK) functionality on any multicore platform with an OpenMP-like runtime. es_ES
dc.description.sponsorship The researchers from Universidad Jaume I were supported by the CICYT Projects TIN2014-53495-R and TIN2017-82972-R of the MINECO and FEDER, and the H2020 EU FETHPC Project 671602 "INTERTWinE". The researchers from Universidad Complutense de Madrid were supported by the CICYT Project TIN2015-65277-R of the MINECO and FEDER. Sandra Catalan was supported during part of this time by the FPU program of the Ministerio de Educacion, Cultura y Deporte. Adrian Castello was supported by the ValI+D 2015 FPI program of the Generalitat Valenciana. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Cluster Computing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Matrix factorizations es_ES
dc.subject Look-ahead es_ES
dc.subject Multi-threading es_ES
dc.subject OpenMP es_ES
dc.subject Lightweight threads es_ES
dc.subject High performance computing es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Programming parallel dense matrix factorizations with look-ahead and OpenMP es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10586-019-02927-z es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/671602/EU/Programming Model INTERoperability ToWards Exascale (INTERTWinE)/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2014-53495-R/ES/COMPUTACION HETEROGENEA DE BAJO CONSUMO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-82972-R/ES/TECNICAS ALGORITMICAS PARA COMPUTACION DE ALTO RENDIMIENTO CONSCIENTE DEL CONSUMO ENERGETICO Y RESISTENTE A ERRORES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2015-65277-R/ES/COMPPUTACION HETEROGENEA EFICIENTE: DEL PROCESADOR AL DATACENTER/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.description.bibliographicCitation Catalán, S.; Castelló, A.; Igual, FD.; Rodríguez-Sánchez, R.; Quintana Ortí, ES. (2020). Programming parallel dense matrix factorizations with look-ahead and OpenMP. Cluster Computing. 23(1):359-375. https://doi.org/10.1007/s10586-019-02927-z es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10586-019-02927-z es_ES
dc.description.upvformatpinicio 359 es_ES
dc.description.upvformatpfin 375 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 23 es_ES
dc.description.issue 1 es_ES
dc.relation.pasarela S\402140 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
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