Energy-efficient allocation of computing node slots in HPC clusters through parameter learning and hybrid genetic fuzzy system modeling

dc.contributor.author	Cocaña Fernández, Alberto
dc.contributor.author	Ranilla Pastor, José
dc.contributor.author	Sánchez Ramos, Luciano
dc.date.accessioned	2015-07-13T11:29:15Z
dc.date.available	2015-07-13T11:29:15Z
dc.date.issued	2015
dc.identifier.citation	Journal of Supercomputing, 71(3), p. 1163-1174 (2015); doi:10.1007/s11227-014-1320-9
dc.identifier.issn	0920-8542
dc.identifier.issn	1573-0484
dc.identifier.uri	http://hdl.handle.net/10651/31740
dc.description.sponsorship	This work has been partially supported by “Ministerio de Economía y Competitividad” from Spain/FEDER under grants TEC2012-38142-C04-04 and TIN2011-24302.
dc.format.extent	p. 1163-1174
dc.language.iso	eng
dc.relation.ispartof	Journal of Supercomputing
dc.rights	© Springer Science+Business Media New York 2014
dc.source	WOS:000350868400019
dc.title	Energy-efficient allocation of computing node slots in HPC clusters through parameter learning and hybrid genetic fuzzy system modeling
dc.type	journal article
dc.identifier.doi	10.1007/s11227-014-1320-9
dc.relation.projectID	MINECO/FEDER/TEC2012-38142-C04-04
dc.relation.projectID	MINECO/FEDER/TIN2011-24302
dc.relation.publisherversion	http://dx.doi.org/10.1007/s11227-014-1320-9

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