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dc.contributor.authorCaheny, Paul
dc.contributor.authorÁlvarez Martí, Lluc
dc.contributor.authorValero Cortés, Mateo
dc.contributor.authorMoretó Planas, Miquel
dc.contributor.authorCasas, Marc
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2018-12-05T08:35:37Z
dc.date.available2018-12-05T08:35:37Z
dc.date.issued2018
dc.identifier.citationCaheny, P., Álvarez, L., Valero, M., Moreto, M., Casas, M. Runtime-assisted cache coherence deactivation in task parallel programs. A: International Conference for High Performance Computing, Networking, Storage, and Analysis. "Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis: Dallas, TX, USA, November 11-16, 2018". New York: Association for Computing Machinery (ACM), 2018, p. 1-12.
dc.identifier.urihttp://hdl.handle.net/2117/125393
dc.description.abstractWith increasing core counts, the scalability of directory-based cache coherence has become a challenging problem. To reduce the area and power needs of the directory, recent proposals reduce its size by classifying data as private or shared, and disable coherence for private data. However, existing classification methods suffer from inaccuracies and require complex hardware support with limited scalability. This paper proposes a hardware/software co-designed approach: the runtime system identifies data that is guaranteed by the programming model semantics to not require coherence and notifies the microarchitecture. The microarchitecture deactivates coherence for this private data and powers off unused directory capacity. Our proposal reduces directory accesses to just 26% of the baseline system, and supports a 64x smaller directory with only 2.8% performance degradation. By dynamically calibrating the directory size our proposal saves 86% of dynamic energy consumption in the directory without harming performance.
dc.description.sponsorshipThis work has been supported by the RoMoL ERC Advanced Grant (GA 321253), by the European HiPEAC Network of Excellence, by the Spanish Ministry of Economy and Competitiveness (contract TIN2015-65316-P), by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272) and by the European Unions Horizon 2020 research and innovation programme (grant agreements 671697 and 779877). M. Moreto has been partially supported by the Spanish Ministry of Economy, Industry and Competitiveness under Ramon y Cajal fellowship number RYC-2016-21104.
dc.format.extent12 p.
dc.language.isoeng
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures paral·leles
dc.subject.lcshMemory management (Computer science)
dc.subject.lcshParallel programming (Computer science)
dc.subject.lcshCache memory
dc.subject.otherMemory architecture
dc.subject.otherRuntime environment
dc.titleRuntime-assisted cache coherence deactivation in task parallel programs
dc.typeConference report
dc.subject.lemacGestió de memòria (Informàtica)
dc.subject.lemacProgramació en paral·lel (Informàtica)
dc.subject.lemacMemòria cau
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://dl.acm.org/citation.cfm?id=3291703
dc.rights.accessOpen Access
local.identifier.drac23529198
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/V PRI/2014 SGR 1272
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/V PRI/2014 SGR 1051
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/RYC-2016-21104
dc.relation.projectidinfo:eu-repo/grantAgreement/HiPEAC (NoE - Unión Europea)/IST-2003-004408
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/321253/EU/Riding on Moore's Law/ROMOL
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/671697/EU/Mont-Blanc 3, European scalable and power efficient HPC platform based on low-power embedded technology/Mont-Blanc 3
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/779877/EU/Mont-Blanc 2020, European scalable, modular and power efficient HPC processor/Mont-Blanc 2020
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2013-2016/RYC-2016-21104
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/
local.citation.authorCaheny, P.; Álvarez, L.; Valero, M.; Moreto, M.; Casas, M.
local.citation.contributorInternational Conference for High Performance Computing, Networking, Storage, and Analysis
local.citation.pubplaceNew York
local.citation.publicationNameProceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis: Dallas, TX, USA, November 11-16, 2018
local.citation.startingPage1
local.citation.endingPage12


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