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A Survey on Malleability Solutions for High-Performance Distributed Computing
dc.contributor.author | Aliaga Estellés, José Ignacio | |
dc.contributor.author | Castillo, Maribel | |
dc.contributor.author | Iserte, Sergio | |
dc.contributor.author | Martín Álvarez, Iker | |
dc.contributor.author | Mayo, Rafael | |
dc.date.accessioned | 2022-09-29T07:28:34Z | |
dc.date.available | 2022-09-29T07:28:34Z | |
dc.date.issued | 2022-05-22 | |
dc.identifier.citation | Aliaga, J.I.; Castillo, M.; Iserte, S.; Martín-Álvarez, I.; Mayo, R. A Survey on Malleability Solutions for High-Performance Distributed Computing. Appl. Sci. 2022, 12, 5231. https://doi.org/10.3390/app12105231 | ca_CA |
dc.identifier.issn | 2076-3417 | |
dc.identifier.uri | http://hdl.handle.net/10234/199982 | |
dc.description.abstract | Maintaining a high rate of productivity, in terms of completed jobs per unit of time, in High-Performance Computing (HPC) facilities is a cornerstone in the next generation of exascale supercomputers. Process malleability is presented as a straightforward mechanism to address that issue. Nowadays, the vast majority of HPC facilities are intended for distributed-memory applications based on the Message Passing (MP) paradigm. For this reason, many efforts are based on the Message Passing Interface (MPI), the de facto standard programming model. Malleability aims to rescale executions on-the-fly, in other words, reconfigure the number and layout of processes in running applications. Process malleability involves resources reallocation within the HPC system, handling processes of the application, and redistributing data among those processes to resume the execution. This manuscript compiles how different frameworks address process malleability, their main features, their integration in resource management systems, and how they may be used in user codes. This paper is a detailed state-of-the-art devised as an entry point for researchers who are interested in process malleability | ca_CA |
dc.format.extent | 32 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | MDPI | ca_CA |
dc.relation | Computación y Comunicaciones de Altas Prestaciones Consciente del Consumo Energético. Aplicaciones al Aprendizaje Profundo Computacional-UJI | ca_CA |
dc.relation.isPartOf | Applied Sciences, 2022, vol. 12, no 10 | ca_CA |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | ca_CA |
dc.subject | exascale | ca_CA |
dc.subject | job reconfiguration | ca_CA |
dc.subject | MPI | ca_CA |
dc.subject | data redistribution | ca_CA |
dc.subject | resource management | ca_CA |
dc.subject | adaptive workloads | ca_CA |
dc.title | A Survey on Malleability Solutions for High-Performance Distributed Computing | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.3390/app12105231 | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://www.mdpi.com/2076-3417/12/10/5231/htm | ca_CA |
dc.description.sponsorship | This research has been funded by the following projects: Project PID2020-113656RB-C21 supported by MCIN/AEI/10.13039/501100011033 and Project UJI-B2019-36 supported by Universitat Jaume I. Researcher S.Iserte was supported by the postdoctoral fellowship APOSTD/2020/026 and researcher I.Martin-Alvarez was supported by the predoctoral fellowship ACIF/2021/260 both from Valencian Region Government and European Social Funds. | |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
project.funder.identifier | http://dx.doi.org/10.13039/501100011033 | ca_CA |
project.funder.name | Ministerio de Ciencia, Innovación y Universidades | ca_CA |
project.funder.name | Universitat Jaume I | ca_CA |
project.funder.name | Generalitat Valenciana | ca_CA |
oaire.awardNumber | MICIU/ICTI2017-2020/PID2020-113656RB-C21 | ca_CA |
oaire.awardNumber | UJI-B2019-36 | ca_CA |
oaire.awardNumber | ACIF/2021/260 | ca_CA |
oaire.awardNumber | APOSTD/2020/026 | ca_CA |
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