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DMR API: Improving cluster productivity by turning applications into malleable

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DMR API: Improving cluster productivity by turning applications into malleable

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Iserte Agut, S.; Mayo Gual, R.; Quintana Ortí, ES.; Beltrán, V.; Peña Monferrer, AJ. (2018). DMR API: Improving cluster productivity by turning applications into malleable. Parallel Computing. 78:54-66. https://doi.org/10.1016/j.parco.2018.07.006

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/147429

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Title: DMR API: Improving cluster productivity by turning applications into malleable
Author: Iserte Agut, Sergio Mayo Gual, Rafael Quintana Ortí, Enrique Salvador Beltrán, Vicenç Peña Monferrer, Antonio José
UPV Unit: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Issued date:
Abstract:
[EN] Adaptive workloads can change on-the-fly the configuration of their jobs, in terms of number of processes. To carry out these job reconfigurations, we have designed a methodology which enables a job to communicate ...[+]
Subjects: MPI malleability , Job reconfiguration , Dynamic reallocation , Smart resource utilization , Adaptive workload
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
Parallel Computing. (issn: 0167-8191 )
DOI: 10.1016/j.parco.2018.07.006
Publisher:
Elsevier
Publisher version: http://doi.org/10.1016/j.parco.2018.07.006
Project ID: info:eu-repo/grantAgreement/EC/H2020/749516/EU
Type: Artículo

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