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dc.contributor.authorGrass, Thomas Dieter
dc.contributor.authorRico Carro, Alejandro
dc.contributor.authorCasas Guix, Marc
dc.contributor.authorMoreto Planas, Miquel
dc.contributor.authorRamírez Bellido, Alejandro
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2015-04-17T18:00:39Z
dc.date.created2015
dc.date.issued2015
dc.identifier.citationGrass, T. [et al.]. Evaluating execution time predictability of task-based programs on multi-core processors. A: International European Conference on Parallel and Distributed Computing. "Euro-Par 2014: Parallel Processing Workshops: Euro-Par 2014 International Workshops: Porto, Portugal: August 25-26, 2014: revised selected papers: part II". Porto: Springer, 2015, p. 218-229.
dc.identifier.isbn978-3-319-14312-5
dc.identifier.urihttp://hdl.handle.net/2117/27448
dc.description.abstractTask-based programming models are becoming increasingly important, as they can reduce the synchronization costs of parallel programs on multi-cores. Instances of the same task type in task-based programs consist of the same code, which leads us to the hypothesis that their performance should be regular and thus their execution time should be predictable. We evaluate this hypothesis for a set of 12 taskbased programs on 4 different machines: a high-end Intel SandyBridge, an IBM POWER7, an ARM Cortex-A9 and an ARM Cortex-A15. We show, that predicting execution time assuming performance regularity can lead to errors of up to 92%. We identify and analyze three sources of execution time impredictability: input dependence, multiple behaviors per task type and resource sharing. We present two models based on linear interpolation and clustering, reducing the prediction error to less than 12% for input dependent task types and to less than 2% for task types with multiple classes of behavior. All in all, this work invalidates the assumption that performance is always regular across instances of the same task type and quantifies its variability on a wide range of benchmarks and multi-core systems.
dc.format.extent12 p.
dc.language.isoeng
dc.publisherSpringer
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures paral·leles
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures paral·leles
dc.subject.lcshParallel processing (Electronic computers)
dc.subject.lcshMultiprocessors
dc.subject.otherExecution Time Predictability
dc.subject.otherMulti-Core
dc.subject.otherTask-Based Programming Models
dc.titleEvaluating execution time predictability of task-based programs on multi-core processors
dc.typeConference report
dc.subject.lemacProcessament en paral·lel (Ordinadors)
dc.subject.lemacMultiprocessadors
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.identifier.doi10.1007/978-3-319-14313-2_19
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://download.springer.com/static/pdf/46/chp%253A10.1007%252F978-3-319-14313-2_19.pdf?auth66=1422547617_373b895e9aa0cfd2cdaafc5d91e61840&ext=.pdf
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac15404264
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/321253/EU/Riding on Moore's Law/ROMOL
dc.date.lift10000-01-01
local.citation.authorGrass, T.; Rico, A.; Casas, M.; Moretó-Planas, M.; Alex Ramirez
local.citation.contributorInternational European Conference on Parallel and Distributed Computing
local.citation.pubplacePorto
local.citation.publicationNameEuro-Par 2014: Parallel Processing Workshops: Euro-Par 2014 International Workshops: Porto, Portugal: August 25-26, 2014: revised selected papers: part II
local.citation.startingPage218
local.citation.endingPage229


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Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain