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dc.contributor.authorD'Amico, Marco
dc.contributor.authorGarcia Gasulla, Marta
dc.contributor.authorLópez, Victor
dc.contributor.authorJokanovic, Ana
dc.contributor.authorSirvent, Raül
dc.contributor.authorCorbalán González, Julita
dc.contributor.otherBarcelona Supercomputing Center
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors
dc.date.accessioned2018-08-23T08:42:45Z
dc.date.available2018-08-23T08:42:45Z
dc.date.issued2018-08-13
dc.identifier.citationD'Amico, M. [et al.]. DROM: Enabling Efficient and Effortless Malleability for Resource Managers. A: "ICPP '18 Proceedings of the 47th International Conference on Parallel Processing Companion". Association for Computing Machinery (ACM), 2018.
dc.identifier.isbn978-1-4503-6523-9
dc.identifier.urihttp://hdl.handle.net/2117/120569
dc.description.abstractIn the design of future HPC systems, research in resource management is showing an increasing interest in a more dynamic control of the available resources. It has been proven that enabling the jobs to change the number of computing resources at run time, i.e. their malleability, can significantly improve HPC system performance. However, job schedulers and applications typically do not support malleability due to the common belief that it introduces additional programming complexity and performance impact. This paper presents DROM, an interface that provides efficient malleability with no effort for program developers. The running application is enabled to adapt the number of threads to the number of assigned computing resources in a completely transparent way to the user through the integration of DROM with standard programming models, such as OpenMP/OmpSs, and MPI. We designed the APIs to be easily used by any programming model, application and job scheduler or resource manager. Our experimental results from two realistic use cases analysis, based on malleability by reducing the number of cores a job is using per node and jobs co-allocation, show the potential of DROM for improving the performance of HPC systems. In particular, the workload of two MPI+OpenMP neuro-simulators are tested, reporting improvement in system metrics, such as total run time and average response time, up to 8% and 48%, respectively.
dc.description.sponsorshipThis work is partially supported by the Span- ish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project, by the Generalitat de Catalunya (contract 2017-SGR-1414) and from the European Union’s Horizon 2020 under grant agreement No 785907 (HBP SGA2)
dc.format.extent10 p.
dc.language.isoeng
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshComputer software
dc.subject.otherSoftware and its engineering
dc.subject.otherSoftware libraries and repositories
dc.titleDROM: Enabling Efficient and Effortless Malleability for Resource Managers
dc.typeConference lecture
dc.subject.lemacProgramació (Ordinadors)
dc.identifier.doi10.1145/3229710.3229752
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://dl.acm.org/citation.cfm?id=3229752
dc.rights.accessOpen Access
local.identifier.drac23436666
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/785907/EU/Human Brain Project Specific Grant Agreement 2/HBP SGA2
local.citation.publicationNameICPP '18 Proceedings of the 47th International Conference on Parallel Processing Companion


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