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dc.contributor.authorUtrera Iglesias, Gladys Miriam
dc.contributor.authorFarreras Esclusa, Montse
dc.contributor.authorFornés de Juan, Jordi
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2019-10-02T11:44:58Z
dc.date.available2021-08-17T00:29:59Z
dc.date.issued2019-12
dc.identifier.citationUtrera, G.; Farreras, M.; Fornés, J. Task Packing: Efficient task scheduling in unbalanced parallel programs to maximize CPU utilization. "Journal of parallel and distributed computing", Desembre 2019, vol. 134, p. 37-49.
dc.identifier.issn0743-7315
dc.identifier.urihttp://hdl.handle.net/2117/169061
dc.description.abstractLoad imbalance in parallel systems can be generated by external factors to the currently running applications like operating system noise or the underlying hardware like a heterogeneous cluster. HPC applications working on irregular data structures can also have difficulties to balance their computations across the parallel tasks. In this article we extend, improve and evaluate more deeply the Task Packing mechanism proposed in a previous work. The main idea of the mechanism is to concentrate the idle cycles of unbalanced applications in such a way that one or more CPUs are freed from execution. To achieve this, CPUs are stressed with just useful work of the parallel application tasks, provided performance is not degraded. The packing is solved by an algorithm based on the Knapsack problem, in a minimum number of CPUs and using oversubscription. We design and implement a more efficient version of such mechanism. To that end, we perform the Task Packing “in place”, taking advantage of idle cycles generated at synchronization points of unbalanced applications. Evaluations are carried out on a heterogeneous platform using FT and miniFE benchmarks. Results showed that our proposal generates low overhead. In addition the amount of freed CPUs are related to a load imbalance metric which can be used as a prediction for it.
dc.format.extent13 p.
dc.language.isoeng
dc.publisherElsevier
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
dc.subject.lcshHigh performance computing
dc.subject.lcshParallel processing (Electronic computers)
dc.subject.lcshCombinatorial optimization
dc.subject.otherMPI
dc.subject.otherHPC
dc.subject.otherOversubscription
dc.subject.otherLoad balancing
dc.subject.otherKnapsack algorithm
dc.titleTask Packing: Efficient task scheduling in unbalanced parallel programs to maximize CPU utilization
dc.typeArticle
dc.subject.lemacCàlcul intensiu (Informàtica)
dc.subject.lemacProcessament en paral·lel (Ordinadors)
dc.subject.lemacOptimització combinatòria
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.identifier.doi10.1016/j.jpdc.2019.08.003
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/abs/pii/S0743731519305623
dc.rights.accessOpen Access
local.identifier.drac25841066
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/6PN/TIN2012-34557
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TIN2015-65316-P
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/V PRI/2014 SGR 1051
local.citation.authorUtrera, G.; Farreras, M.; Fornés, J.
local.citation.publicationNameJournal of parallel and distributed computing
local.citation.volume134
local.citation.startingPage37
local.citation.endingPage49


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