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dc.date.accessioned 2011-08-31T13:47:19Z
dc.date.available 2011-08-31T03:00:00Z
dc.date.issued 2010-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/9686
dc.description.abstract In order to measure the performance of a parallel machine, a set of application kernels as benchmarks have often been used. However, it is not always possible to characterize the performance using only benchmarks, given the fact that each one usually reflects a narrow set of kernel applications at best. Computers show different performance indices for different applications as they run them. Accurate prediction of parallel applications’ performance is becoming increasingly complex and the time required to run it thoroughly is an onerous requirement; especially if we want to predict for different systems. In production clusters, where throughput and efficiency of use are fundamental, it is important to be able to predict which system is more appropriate for an application, or how long a scheduled application will take to run, in order to have the foresight that will allow us to make better use of the resources available. en
dc.format.extent 155-156 es
dc.language en es
dc.subject Parallel es
dc.title Parallel Application Signature for Performance Prediction en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct10-TO3.pdf es
sedici.identifier.issn 1666-6038 es
sedici.title.subtitle Ph. D. Thesis in High Perfomance Computing en
sedici.creator.person Wong, Alvaro es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Revision 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 non-peer-review es
sedici2003.identifier ARG-UNLP-REV-0000000438 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 10, no. 3 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)