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dc.contributor.authorGonzález-Domínguez, Jorge
dc.contributor.authorExpósito, Roberto R.
dc.date.accessioned2023-12-15T10:22:24Z
dc.date.available2023-12-15T10:22:24Z
dc.date.issued2018
dc.identifier.citationGonzález-Domínguez J, Expósito RR (2018). ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems. PLoS ONE 13(4): e0194361. https://doi.org/10.1371/journal.pone.0194361es_ES
dc.identifier.urihttp://hdl.handle.net/2183/34515
dc.description.abstract[Abstract]: Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, a parallel tool to accelerate the search of interesting biclusters on binary datasets, which are very popular on different fields such as genetics, marketing or text mining. It is based on the state-of-the-art sequential Java tool BiBit, which has been proved accurate by several studies, especially on scenarios that result on many large biclusters. ParBiBit uses the same methodology as BiBit (grouping the binary information into patterns) and provides the same results. Nevertheless, our tool significantly improves performance thanks to an efficient implementation based on C++11 that includes support for threads and MPI processes in order to exploit the compute capabilities of modern distributed-memory systems, which provide several multicore CPU nodes interconnected through a network. Our performance evaluation with 18 representative input datasets on two different eight-node systems shows that our tool is significantly faster than the original BiBit. Source code in C++ and MPI running on Linux systems as well as a reference manual are available at https://sourceforge.net/projects/parbibit/.es_ES
dc.description.sponsorshipThis work was supported by the Ministry of Economy, Industry and Competitiveness of Spain and FEDER funds of the European Union [grant TIN2016-75845-P (AEI/FEDER/UE)], as well as by Xunta de Galicia (Centro Singular de Investigacion de Galicia accreditation 2016-2019, ref. EDG431G/01).es_ES
dc.description.sponsorshipXunta de Galicia; EDG431G/01es_ES
dc.language.isoenges_ES
dc.publisherPLoSes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2016-75845-P/ES/NUEVOS DESAFIOS EN COMPUTACION DE ALTAS PRESTACIONES: DESDE ARQUITECTURAS HASTA APLICACIONES (II)/es_ES
dc.relation.urihttps://doi.org/10.1371/journal.pone.0194361es_ES
dc.rightsAtribución 4.0 International (CC BY 4.0 DEED)es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectBiclusteringes_ES
dc.subjectMPIes_ES
dc.subjectMulticore clusterses_ES
dc.titleParBiBit: Parallel tool for binary biclustering on modern distributed-memory systemses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitlePLoS ONEes_ES
UDC.volume13es_ES
UDC.issue4es_ES
UDC.startPagee0194361es_ES
dc.identifier.doi10.1371/journal.pone.0194361


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