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dc.contributor.authorAlonso, Fernando
dc.contributor.authorGonzález Escribano, Arturo 
dc.contributor.authorTorres, Yuri
dc.contributor.authorLlanos Ferraris, Diego Rafael 
dc.contributor.editorCMMSE 2019es
dc.date.accessioned2019-11-05T18:38:30Z
dc.date.available2019-11-05T18:38:30Z
dc.date.issued2019
dc.identifier.citationCoarse-grain Load Distribution in Heterogeneous Computing. Fernando Alonso, Arturo González-Escribano, Yuri Torres, Diego R. Llanos. Tipo de Participación: poster. 19th International Computational and Mathematical Methods in Science and Engineering 2019 – CMMSE 2019, Costa Ballena (Rota), Cádiz (España). Fecha: 1-5 julio 2019.es
dc.identifier.urihttp://uvadoc.uva.es/handle/10324/39043
dc.description.abstractHPC heterogeneous clusters are composed by different type of machines (various types of component manufacturers, varying computational capacities), and different hardware accelerators. TThe most common type of data distributions is the equal division of the data across all the nodes. A more sophisticated policy of data distribution is needed to explode the computational capacity of the entire system.es
dc.format.mimetypeapplication/pdfes
dc.language.isospaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.titleCoarse-grain Load Distribution in Heterogeneous Computinges
dc.typeinfo:eu-repo/semantics/otheres
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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