A Survey on Malleability Solutions for High-Performance Distributed Computing
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Title
A Survey on Malleability Solutions for High-Performance Distributed ComputingAuthor (s)
Date
2022-05-22Publisher
MDPIISSN
2076-3417Bibliographic 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/app12105231Type
info:eu-repo/semantics/articlePublisher version
https://www.mdpi.com/2076-3417/12/10/5231/htmVersion
info:eu-repo/semantics/publishedVersionSubject
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 mallea ... [+]
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 [-]
Is part of
Applied Sciences, 2022, vol. 12, no 10Funder Name
Ministerio de Ciencia, Innovación y Universidades | Universitat Jaume I | Generalitat Valenciana
Funder ID
http://dx.doi.org/10.13039/501100011033
Project code
MICIU/ICTI2017-2020/PID2020-113656RB-C21 | UJI-B2019-36 | ACIF/2021/260 | APOSTD/2020/026
Project title or grant
Computación y Comunicaciones de Altas Prestaciones Consciente del Consumo Energético. Aplicaciones al Aprendizaje Profundo Computacional-UJI
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info:eu-repo/semantics/openAccess
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