TY - GEN
T1 - Automated performance modeling of the UG4 simulation framework
AU - Vogel, Andreas
AU - Calotoiu, Alexandru
AU - Nägel, Arne
AU - Reiter, Sebastian
AU - Strube, Alexandre
AU - Wittum, Gabriel
AU - Wolf, Felix
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - 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. (ComputVis 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.
AB - 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. (ComputVis 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.
UR - http://www.scopus.com/inward/record.url?scp=84989831287&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-40528-5_21
DO - 10.1007/978-3-319-40528-5_21
M3 - Conference contribution
AN - SCOPUS:84989831287
SN - 9783319405261
T3 - Lecture Notes in Computational Science and Engineering
SP - 467
EP - 481
BT - Software for Exascale Computing - SPPEXA 2013-2015
A2 - Nagel, Wolfgang E.
A2 - Bungartz, Hans-Joachim
A2 - Neumann, Philipp
PB - Springer Verlag
T2 - International Conference on Software for Exascale Computing, SPPEXA 2015
Y2 - 25 January 2016 through 27 January 2016
ER -