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dc.contributor.authorTan, Xubin
dc.contributor.authorBosch, Jaume
dc.contributor.authorÁlvarez, Carlos
dc.contributor.authorJiménez González, Daniel
dc.contributor.authorAyguadé Parra, Eduard
dc.contributor.authorValero Cortés, Mateo
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2019-11-26T08:18:47Z
dc.date.available2019-11-26T08:18:47Z
dc.date.issued2019-09-01
dc.identifier.citationTan, X. [et al.]. A hardware runtime for task-based programming models. "IEEE transactions on parallel and distributed systems", 1 Setembre 2019, vol. 30, núm. 9, p. 1932-1946.
dc.identifier.issn1045-9219
dc.identifier.urihttp://hdl.handle.net/2117/173031
dc.description© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstractTask-based programming models such as OpenMP 5.0 and OmpSs are simple to use and powerful enough to exploit task parallelism of applications over multicore, manycore and heterogeneous systems. However, their software-only runtimes introduce relevant overhead when targeting fine-grained tasks, resulting in performance losses. To overcome this drawback, we present a hardware runtime Picos++ that accelerates critical runtime functions such as task dependence analysis, nested task support, and heterogeneous task scheduling. As a proof-of-concept, the Picos++ hardware runtime has been integrated with a compiler infrastructure that supports parallel task-based programming models. A FPGA SoC running Linux OS has been used to implement the hardware accelerated part of Picos++, integrated with a heterogeneous system composed of 4 symmetric multiprocessor (SMP) cores and several hardware functional accelerators (HwAccs) for task execution. Results show significant improvements on energy and performance compared to state-of-the-art parallel software-only runtimes. With Picos++, applications can achieve up to 7.6x speedup and save up to 90 percent of energy, when using 4 threads and up to 4 HwAccs, and even reach a speedup of 16x over the software alternative when using 12 HwAccs and small tasks.
dc.format.extent15 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures paral·leles
dc.subject.lcshField programmable gate arrays
dc.subject.lcshMultiprocessors
dc.subject.lcshParallel processing (Electronic computers)
dc.subject.otherFine-grained parallelism
dc.subject.otherTask-dependence analysis
dc.subject.otherNested tasks
dc.subject.otherHeterogeneous task scheduling
dc.subject.otherEnergy saving
dc.subject.otherFPGA
dc.subject.otherTask-based programming models
dc.titleA hardware runtime for task-based programming models
dc.typeArticle
dc.subject.lemacMatrius de portes programables per l'usuari
dc.subject.lemacMultiprocessadors
dc.subject.lemacProcessament en paral·lel (Ordinadors)
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.identifier.doi10.1109/TPDS.2019.2907493
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8674567
dc.rights.accessOpen Access
local.identifier.drac25846693
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/2017-SGR-1328
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/2017 SGR 1414
local.citation.authorTan, X.; Bosch, J.; Álvarez, C.; Jimenez, D.; Ayguade, E.; Valero, M.
local.citation.publicationNameIEEE transactions on parallel and distributed systems
local.citation.volume30
local.citation.number9
local.citation.startingPage1932
local.citation.endingPage1946


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