Efficient data redistribution for malleable applications
Ver/ Abrir
Impacto
Scholar |
Otros documentos de la autoría: Martín Álvarez, Iker; Aliaga Estellés, José Ignacio; Castillo, Maribel; Iserte, Sergio
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/146069
comunitat-uji-handle4:
INVESTIGACIONMetadatos
Título
Efficient data redistribution for malleable applicationsFecha de publicación
2023Editor
ACM Digital Library; Association for Computing MachineryISBN
979840070785Cita bibliográfica
MARTÍN ÁLVAREZ, Iker, et al. Efficient data redistribution for malleable applications. In: Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis. 2023. p. 416-426Tipo de documento
info:eu-repo/semantics/conferenceObjectVersión de la editorial
https://dl.acm.org/doi/10.1145/3624062.3624110Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Process malleability can be defined as the ability of a distributed MPI parallel job to change the number of processes on–the–fly without stopping its execution, reallocating the compute resources originally assigned ... [+]
Process malleability can be defined as the ability of a distributed MPI parallel job to change the number of processes on–the–fly without stopping its execution, reallocating the compute resources originally assigned to the job, and without storing application data to disk. MPI malleability consists of four stages: resource reallocation, process management, data redistribution and execution resuming. Among them, data redistribution is the most time-consuming and determines the reconfiguration time. In this paper, we compare different implementations of this stage using point-to-point and collective MPI operations, and discuss the impact of overlapping computation-communication. We then combine these strategies with different methods to expand/shrink jobs, using a synthetic application to emulate MPI-based codes and their malleable counterparts, in order to evaluate the effect of different malleability methods in parallel distributed applications. The results show that the use of asynchronous techniques speeds up execution by 1.14 and 1.21, depending on the network used. [-]
Descripción
In Workshops of The International Conference on High Performance Computing, Network, Storage,
and Analysis (SC-W 2023), November 12–17, 2023, Denver, CO, USA. ACM, New York, NY, USA.
Publicado en
In: Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis. 2023. p. 416-426.Entidad financiadora
Ministerio de Ciencia, Innovación y Universidades | Agencia Estatal de Investigación | Generalitat Valenciana | Comisión Europea | Unión Europea | Ministerio de Pesca | European Union NextGenera-tionEU/PRTR
Código del proyecto o subvención
PID2020-113656RB-C21 | ACIF/2021/260 | 955606 | PCI2021-121958
Derechos de acceso
info:eu-repo/semantics/openAccess