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dc.contributor.authorCano-Cano, Javier
dc.contributor.authorAndújar, Francisco J.
dc.contributor.authorAlfaro, Francisco J.
dc.contributor.authorSánchez, José L.
dc.date.accessioned2025-01-30T17:30:04Z
dc.date.available2025-01-30T17:30:04Z
dc.date.issued2019
dc.identifier.citationJournal of Parallel and Distributed Computing, Volume 133, 2019, Pages 124-135,es
dc.identifier.issn0743-7315es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/74693
dc.descriptionProducción Científicaes
dc.description.abstractSimulation is used to evaluate and validate the behavior and performance of computing systems, in particular the interconnection network in the context of high-performance computing. For the simulation to be performed, the simulator program must be provided with a mechanism that generates network traffic or workload. Although synthetic traffic has been widely used, communication from real applications is a better and more representative workload. With this kind of network workload, the simulations can become slower, especially when simulating Exascale systems. In this paper, we extend the VEF trace framework, originally designed for feeding off-chip networks with MPI traffic, including new functionality related to the on-chip communications and introducing improvements to speed up the simulations. This way, the VEF framework allows to study the behavior of Exascale interconnection networks with realistic traffic and in reasonably short timees
dc.format.mimetypeapplication/pdfes
dc.language.isospaes
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses
dc.titleSpeeding up exascale interconnection network simulations with the VEF3 trace frameworkes
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.1016/j.jpdc.2019.06.013es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0743731519304782es
dc.identifier.publicationfirstpage124es
dc.identifier.publicationlastpage135es
dc.identifier.publicationtitleJournal of Parallel and Distributed Computinges
dc.identifier.publicationvolume133es
dc.peerreviewedSIes
dc.description.projectThis work has been supported by the Junta de Comunidades Castilla-La Mancha, European Commission (FEDER funds) and Ministerio de Ciencia, Innovación y Universidades under projects SBPLY/17/180501/000498 and RTI2018-098156-B-C52 respectively. It is also co-financed by the University of Castilla-La Mancha and Fondo Europeo de Desarrollo Regional funds under project 2019-GRIN-27060. Javier Cano-Cano is also funded by the MINECO under FPI grant BES-2016-078800.es
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones


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