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dc.date.accessioned 2008-05-21T19:17:42Z
dc.date.available 2008-05-21T03:00:00Z
dc.date.issued 2007-04
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/9526
dc.description.abstract This paper discusses automatic mapping methods for concurrent tasks to processors applying graph analysis for the relation among tasks, in which processing and communicating times are incorporated. Starting by an analysis in which processors are homogeneous and data transmission times do not depend on the processors that are communicating (a typical case in homogeneous clusters), we progress to extend the model to heterogeneous processors having the possibility of different communication levels, applicable to a multicluster. Some results obtained with the model and future work lines are presented, particularly, the possibility of obtaining the required optimal number of processors, keeping a constant efficiency level. en
dc.format.extent 39-44 es
dc.language en es
dc.subject Parallel es
dc.subject Modeling and prediction es
dc.title A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Mar07-7.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person De Giusti, Laura Cristina es
sedici.creator.person Chichizola, Franco es
sedici.creator.person Naiouf, Marcelo es
sedici.creator.person Ripoll, Ana es
sedici.creator.person De Giusti, Armando Eduardo es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000000574 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 7, no. 1 es


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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)