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Task Packing: Efficient task scheduling in unbalanced parallel programs to maximize CPU utilization
dc.contributor.author | Utrera Iglesias, Gladys Miriam |
dc.contributor.author | Farreras Esclusa, Montse |
dc.contributor.author | Fornés de Juan, Jordi |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.date.accessioned | 2019-10-02T11:44:58Z |
dc.date.available | 2021-08-17T00:29:59Z |
dc.date.issued | 2019-12 |
dc.identifier.citation | Utrera, 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.issn | 0743-7315 |
dc.identifier.uri | http://hdl.handle.net/2117/169061 |
dc.description.abstract | Load 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.extent | 13 p. |
dc.language.iso | eng |
dc.publisher | Elsevier |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors |
dc.subject.lcsh | High performance computing |
dc.subject.lcsh | Parallel processing (Electronic computers) |
dc.subject.lcsh | Combinatorial optimization |
dc.subject.other | MPI |
dc.subject.other | HPC |
dc.subject.other | Oversubscription |
dc.subject.other | Load balancing |
dc.subject.other | Knapsack algorithm |
dc.title | Task Packing: Efficient task scheduling in unbalanced parallel programs to maximize CPU utilization |
dc.type | Article |
dc.subject.lemac | Càlcul intensiu (Informàtica) |
dc.subject.lemac | Processament en paral·lel (Ordinadors) |
dc.subject.lemac | Optimització combinatòria |
dc.contributor.group | Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
dc.identifier.doi | 10.1016/j.jpdc.2019.08.003 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/abs/pii/S0743731519305623 |
dc.rights.access | Open Access |
local.identifier.drac | 25841066 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO/6PN/TIN2012-34557 |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/ |
dc.relation.projectid | info:eu-repo/grantAgreement/AGAUR/V PRI/2014 SGR 1051 |
local.citation.author | Utrera, G.; Farreras, M.; Fornés, J. |
local.citation.publicationName | Journal of parallel and distributed computing |
local.citation.volume | 134 |
local.citation.startingPage | 37 |
local.citation.endingPage | 49 |
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