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dc.date.accessioned 2012-11-05T14:01:29Z
dc.date.available 2012-11-05T14:01:29Z
dc.date.issued 2012-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23630
dc.description.abstract Energy consumption has become one of the greatest challenges in the eld of High Performance Computing (HPC). Besides its impact on the environment, energy is a limiting factor for the HPC. Keeping the power consumption of a system below a threshold is one of the great problems; and power prediction can help to solve it. The power characterisation can be used to know the power behaviour of the system under study, and to be a support to reach the power prediction. Furthermore, it could be used to design power-aware application programs. In this article we propose a methodology to characterise the power consumption of shared-memory HPC systems. Our proposed methodology involves the nding of in uence factors on power consumed by the systems. It is similar to previous works, but we propose an in-deep approach that can help us to get a better power characterisation of the system. We apply our methodology to characterise an Intel server platform and the results show that we can nd a more extended set of in uence factors on power consumption. en
dc.language en es
dc.subject Power Characterisation en
dc.subject Distributed es
dc.subject Shared-Memory en
dc.subject Parallel es
dc.subject HPC Systems en
dc.title Power characterisation of shared-memory hpc systems en
dc.type Objeto de conferencia es
sedici.creator.person Balladini, Javier es
sedici.creator.person Rucci, Enzo es
sedici.creator.person De Giusti, Armando Eduardo es
sedici.creator.person Naiouf, Marcelo es
sedici.creator.person Suppi, Remo es
sedici.creator.person Rexachs del Rosario, Dolores es
sedici.creator.person Luque Fadón, Emilio es
sedici.description.note Eje: Workshop Procesamiento distribuido y paralelo (WPDP) es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2012-10
sedici.relation.event XVIII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)