Coarse-grain Load Distribution in Heterogeneous Computing

Título

dc.contributor.author	Alonso, Fernando
dc.contributor.author	González Escribano, Arturo
dc.contributor.author	Torres de la Sierra, Yuri
dc.contributor.author	Llanos Ferraris, Diego Rafael
dc.contributor.editor	CMMSE 2019	es
dc.date.accessioned	2019-11-05T18:38:30Z
dc.date.available	2019-11-05T18:38:30Z
dc.date.issued	2019
dc.identifier.citation	Coarse-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.uri	http://uvadoc.uva.es/handle/10324/39043
dc.description.abstract	HPC 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.mimetype	application/pdf	es
dc.language.iso	spa	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.title	Coarse-grain Load Distribution in Heterogeneous Computing	es
dc.type	info:eu-repo/semantics/other	es
dc.type.hasVersion	info:eu-repo/semantics/publishedVersion	es