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Automated Performance Modeling of the UG4 Simulation Framework

Vogel, Andreas ; Calotoiu, Alexandru ; Nagel, Arne ; Reiter, Sebastian ; Strube, Alexandre ; Wittum, Gabriel ; Wolf, Felix (2016)
Automated Performance Modeling of the UG4 Simulation Framework.
SPPEXA Symposium 2016. Munich, Germany (25.-27.01.2016)
doi: 10.1007/978-3-319-40528-5_21
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Many scientific research questions such as the drug diffusion through the upper part of the human skin are formulated in terms of partial differential equations and their solution is numerically addressed using grid based finite element methods. For detailed and more realistic physical models this computational task becomes challenging and thus complex numerical codes with good scaling properties up to millions of computing cores are required. Employing empirical tests we presented very good scaling properties for the geometric multigrid solver in Reiter et al. (Comput Vis Sci 16(4):151–164, 2013) using the UG4 framework that is used to address such problems. In order to further validate the scalability of the code we applied automated performance modeling to UG4 simulations and presented how performance bottlenecks can be detected and resolved in Vogel et al. (10,000 performance models per minute—scalability of the UG4 simulation framework. In: Träff JL, Hunold S, Versaci F (eds) Euro-Par 2015: Parallel processing, theoretical computer science and general issues, vol 9233. Springer, Springer, Heidelberg, pp 519–531, 2015). In this paper we provide an overview on the obtained results, present a more detailed analysis via performance models for the components of the geometric multigrid solver and comment on how the performance models coincide with our expectations.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2016
Autor(en): Vogel, Andreas ; Calotoiu, Alexandru ; Nagel, Arne ; Reiter, Sebastian ; Strube, Alexandre ; Wittum, Gabriel ; Wolf, Felix
Art des Eintrags: Bibliographie
Titel: Automated Performance Modeling of the UG4 Simulation Framework
Sprache: Englisch
Publikationsjahr: 15 September 2016
Verlag: Springer
Buchtitel: Software for Exascale Computing - SPPEXA 2013-2015
Reihe: Lecture Notes in Computational Science and Engineering
Band einer Reihe: 113
Veranstaltungstitel: SPPEXA Symposium 2016
Veranstaltungsort: Munich, Germany
Veranstaltungsdatum: 25.-27.01.2016
Auflage: 1st Edition
DOI: 10.1007/978-3-319-40528-5_21
Kurzbeschreibung (Abstract):

Many scientific research questions such as the drug diffusion through the upper part of the human skin are formulated in terms of partial differential equations and their solution is numerically addressed using grid based finite element methods. For detailed and more realistic physical models this computational task becomes challenging and thus complex numerical codes with good scaling properties up to millions of computing cores are required. Employing empirical tests we presented very good scaling properties for the geometric multigrid solver in Reiter et al. (Comput Vis Sci 16(4):151–164, 2013) using the UG4 framework that is used to address such problems. In order to further validate the scalability of the code we applied automated performance modeling to UG4 simulations and presented how performance bottlenecks can be detected and resolved in Vogel et al. (10,000 performance models per minute—scalability of the UG4 simulation framework. In: Träff JL, Hunold S, Versaci F (eds) Euro-Par 2015: Parallel processing, theoretical computer science and general issues, vol 9233. Springer, Springer, Heidelberg, pp 519–531, 2015). In this paper we provide an overview on the obtained results, present a more detailed analysis via performance models for the components of the geometric multigrid solver and comment on how the performance models coincide with our expectations.

Freie Schlagworte: DFG|SPPEXA 1648
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Parallele Programmierung
Hinterlegungsdatum: 20 Apr 2018 12:22
Letzte Änderung: 01 Mär 2024 10:28
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