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dc.contributor.authorAndrade, Diego
dc.contributor.authorFraguela, Basilio B.
dc.contributor.authorDoallo, Ramón
dc.date.accessioned2023-11-30T15:35:48Z
dc.date.available2023-11-30T15:35:48Z
dc.date.issued2018
dc.identifier.citationAndrade, D., Fraguela, B.B., Doallo, R. (2018). Guiding the Optimization of Parallel Codes on Multicores Using an Analytical Cache Model. In: Shi, Y., et al. Computational Science – ICCS 2018. ICCS 2018. Lecture Notes in Computer Science(), vol 10862. Springer, Cham. https://doi.org/10.1007/978-3-319-93713-7_32es_ES
dc.identifier.urihttp://hdl.handle.net/2183/34393
dc.descriptionVersión final aceptada de: https://doi.org/10.1007/978-3-319-93713-7_32es_ES
dc.descriptionThis is a post-peer-review, pre-copyedit version of an article published in Lecture Notes on Computer Science (ICCS 2018 proceedings). The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-93713-7_32es_ES
dc.description.abstract[Abstract]: Cache performance is particularly hard to predict in modern multicore processors as several threads can be concurrently in execution, and private cache levels are combined with shared ones. This paper presents an analytical model able to evaluate the cache performance of the whole cache hierarchy for parallel applications in less than one second taking as input their source code and the cache configuration. While the model does not tackle some advanced hardware features, it can help optimizers to make reasonably good decisions in a very short time. This is supported by an evaluation based on two modern architectures and three different case studies, in which the model predictions differ on average just 5.05% from the results of a detailed hardware simulator and correctly guide different optimization decisions.es_ES
dc.description.sponsorshipThis research was supported by the Ministry of Economy and Competitiveness of Spain and FEDER funds (80%) of the EU (TIN2016-75845-P), and by the Government of Galicia (Xunta de Galicia) co-founded by the European Regional Development Fund (ERDF) under the Consolidation Programme of Competitive Reference Groups (ED431C 2017/04) as well as under the Centro Singular de Investigación de Galicia accreditation 2016-2019 (ED431G/01). We also acknowledge the Centro de Supercomputación de Galicia (CESGA) for the use of their computers.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2017/04es_ES
dc.description.sponsorshipXunta de Galicia; ED431G/01es_ES
dc.language.isoenges_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2016-75845-P/ES/NUEVOS DESAFIOS EN COMPUTACION DE ALTAS PRESTACIONES: DESDE ARQUITECTURAS HASTA APLICACIONES (II)/es_ES
dc.relation.isversionofhttps://doi.org/10.1007/978-3-319-93713-7_32
dc.relation.urihttps://doi.org/10.1007/978-3-319-93713-7_32es_ES
dc.rightsTodos os dereitos reservados. All rights reserved.es_ES
dc.subjectAnalytical Cache Modeles_ES
dc.subjectMulticore processorses_ES
dc.subjectCache performancees_ES
dc.subjectOptimizationes_ES
dc.titleGuiding the Optimization of Parallel Codes on Multicores Using an Analytical Cache Modeles_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1007/978-3-319-93713-7_32


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