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Erschienen in: The Journal of Supercomputing 7/2020

23.01.2020

Legacy code and parallel computing: updating and parallelizing a numerical model

verfasst von: Fernando G. Tinetti, Maximiliano J. Perez, Ariel Fraidenraich, Adolfo E. Altenberg

Erschienen in: The Journal of Supercomputing | Ausgabe 7/2020

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Abstract

In this paper, we present several important details in the process of legacy code parallelization, mostly related to the problem of maintaining numerical output of a legacy code while obtaining a balanced workload for parallel processing. Since we maintained the non-uniform mesh imposed by the original finite element code, we have to develop a specially designed data distribution among processors so that data restrictions are met in the finite element method. In particular, we introduce a data distribution method that is initially used in shared memory parallel processing and obtain better performance than the previous parallel program version. Besides, this method can be extended to other parallel platforms such as distributed memory parallel computers. We present results including several problems related to performance profiling on different (development and production) parallel platforms. The use of new and old parallel computing architectures leads to different behavior of the same code, which in all cases provides better performance in multiprocessor hardware.

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Metadaten
Titel
Legacy code and parallel computing: updating and parallelizing a numerical model
verfasst von
Fernando G. Tinetti
Maximiliano J. Perez
Ariel Fraidenraich
Adolfo E. Altenberg
Publikationsdatum
23.01.2020
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 7/2020
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-020-03172-7

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