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Erschienen in: Software and Systems Modeling 1/2018

14.03.2016 | Regular Paper

On the use of models for high-performance scientific computing applications: an experience report

verfasst von: Ileana Ober, Marc Palyart, Jean-Michel Bruel, David Lugato

Erschienen in: Software and Systems Modeling | Ausgabe 1/2018

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Abstract

This paper reports on a four-year project that aims to raise the abstraction level through the use of model-driven engineering (MDE) techniques in the development of scientific applications relying on high-performance computing. The development and maintenance of high-performance scientific computing software is reputedly a complex task. This complexity results from the frequent evolutions of supercomputers and the tight coupling between software and hardware aspects. Moreover, current parallel programming approaches result in a mixing of concerns within the source code. Our approach relies on the use of MDE and consists in defining domain-specific modeling languages targeting various domain experts involved in the development of HPC applications, allowing each of them to handle their dedicated model in a both user-friendly and hardware-independent way. The different concerns are separated thanks to the use of several models as well as several modeling viewpoints on these models. Depending on the targeted execution platforms, these abstract models are translated into executable implementations by means of model transformations. To make all of these effective, we have developed a tool chain that is also presented in this paper. The approach is assessed through a multi-dimensional validation that focuses on its applicability, its expressiveness and its efficiency. To capitalize on the gained experience, we analyze some lessons learned during this project.

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Fußnoten
2
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Metadaten
Titel
On the use of models for high-performance scientific computing applications: an experience report
verfasst von
Ileana Ober
Marc Palyart
Jean-Michel Bruel
David Lugato
Publikationsdatum
14.03.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Software and Systems Modeling / Ausgabe 1/2018
Print ISSN: 1619-1366
Elektronische ISSN: 1619-1374
DOI
https://doi.org/10.1007/s10270-016-0518-0

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