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dc.contributor.authorGrass, Thomas
dc.contributor.authorAllande, César
dc.contributor.authorArmejach, Adrià
dc.contributor.authorRico, Alejandro
dc.contributor.authorAyguadé Parra, Eduard
dc.contributor.authorLabarta, Jesús
dc.contributor.authorValero Cortés, Mateo
dc.contributor.authorCasas, Marc
dc.contributor.authorMoreto Planas, Miquel
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2017-01-13T09:01:31Z
dc.date.issued2016
dc.identifier.citationGrass, T., Allande, C., Armejach, A., Rico, A., Ayguade, E., Labarta, J., Valero, M., Casas, M., Moreto, M. MUSA: a multi-level simulation approach for next-generation HPC machines. A: International Conference for High Performance Computing, Networking, Storage and Analysis. "SC'16: International Conference for High Performance Computing, Networking, Storage and Analysis: proceedings: Salt Lake City, UT, USA: November 13-18, 2016". Salt Lake City, UT: Institute of Electrical and Electronics Engineers (IEEE), 2016.
dc.identifier.isbn978-1-4673-8815-3
dc.identifier.urihttp://hdl.handle.net/2117/99179
dc.description.abstractThe complexity of High Performance Computing (HPC) systems is increasing in the number of components and their heterogeneity. Interactions between software and hardware involve many different aspects which are typically not transparent to scientific programmers and system architects. Therefore, predicting the behavior of current scientific applications on future HPC infrastructures is a challenging task. In this paper we present MUSA, an end-to-end methodology that employs a multi-level simulation infrastructure. By combining different levels of abstraction, MUSA is able to model the communication network, microarchitectural details and system software interactions, providing different trade-offs in terms of simulation cost and accuracy. We compare detailed MUSA simulations with native executions of up to 2,048 cores and find relative errors that are within 10% in the common case. In addition, we use MUSA to simulate up to 16,384 cores and successfully identify scalability bottlenecks due to different factors, e.g. memory contention or load imbalance. We also compare different system configurations, showing how MUSA can help system designers to assess the usefulness of future technologies in next-generation HPC machines.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshHigh performance computing
dc.subject.otherHigh Performance Computing (HPC)
dc.subject.otherMulti-level simulation infrastructure
dc.subject.otherSimulation Time Cost Analysis
dc.titleMUSA: a multi-level simulation approach for next-generation HPC machines
dc.typeConference report
dc.subject.lemacCàlcul intensiu (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://dl.acm.org/citation.cfm?id=3014965
dc.rights.accessRestricted access - publisher's policy
drac.iddocument19344758
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TIN2015-65316-P
dc.relation.projectidinfo:eu-repo/grantAgreement/SEV-2015-0493
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 platformbased on low-power embedded technology/Mont-Blanc 3
dc.date.lift10000-01-01
upcommons.citation.authorGrass, T., Allande, C., Armejach, A., Rico, A., Ayguade, E., Labarta, J., Valero, M., Casas, M., Moreto, M.
upcommons.citation.contributorInternational Conference for High Performance Computing, Networking, Storage and Analysis
upcommons.citation.pubplaceSalt Lake City, UT
upcommons.citation.publishedtrue
upcommons.citation.publicationNameSC'16: International Conference for High Performance Computing, Networking, Storage and Analysis: proceedings: Salt Lake City, UT, USA: November 13-18, 2016


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