PARCSIM: a parallel computing simulator for scalable software optimization

PARCSIM is a parallel software simulator that allows a user to capture, through a graphical interface, matrix algorithm schemes that solve scientific problems. With this tool, the user can analyse the execution times that would be obtained by using different spatio-temporal mapping of computational...

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Vydané v:The Journal of supercomputing Ročník 78; číslo 15; s. 17231 - 17246
Hlavní autori: Cámara, Jesús, Cano, José-Carlos, Cuenca, Javier, Saura-Sánchez, Mariano
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.10.2022
Springer Nature B.V
Predmet:
Algorithms
CMMSE- Computational and Mathematical methods
Compilers
Computer Science
Hardware
Interpreters
Mapping
Optimization
Processor Architectures
Programming Languages
Simulation
Software
Polyalgorithm
Autotuning
Hierarchical parallel software
ISSN:0920-8542, 1573-0484
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Popis
Shrnutí:PARCSIM is a parallel software simulator that allows a user to capture, through a graphical interface, matrix algorithm schemes that solve scientific problems. With this tool, the user can analyse the execution times that would be obtained by using different spatio-temporal mapping of computational tasks on available computational units, parallelism parameters and computational libraries. Furthermore, for complex problem models, the self-optimization engine incorporated in this tool analyses the huge tree of possible calculations grouping and mapping strategies in search of the choice that makes the best use of the available hardware resources. This tool also offers polyalgorithmic resolution by making automatically the best decision between different software approaches to solve a given problem on the hardware system available. This work shows the usefulness of this simulator to efficiently solve hierarchical problems constructed from previously modelled subproblems. This task is performed by reusing, in a scalable way, the optimization information of these subproblems to establish the best execution configuration for the composite problem.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-022-04537-w