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@INBOOK{Vogel:820613,
author = {Vogel, Andreas and Calotoiu, Alexandru and Nägel, Arne and
Reiter, Sebastian and Strube, Alexandre and Wittum, Gabriel
and Wolf, Felix},
title = {{A}utomated {P}erformance {M}odeling of the {UG}4
{S}imulation {F}ramework},
volume = {113},
address = {Cham, Switzerland},
publisher = {Springer International Publishing},
reportid = {FZJ-2016-05885},
isbn = {978-3-319-40526-1},
series = {Lecture Notes in Computational Science and Engineering},
pages = {467 - 481},
year = {2016},
comment = {Software for Exascale Computing - SPPEXA 2013-2015 /
Bungartz, Hans-Joachim (Editor) ; Chapter 21 ; ISBN:
978-3-319-40526-1=978-3-319-40528-5},
booktitle = {Software for Exascale Computing -
SPPEXA 2013-2015 / Bungartz,
Hans-Joachim (Editor) ; Chapter 21 ;
ISBN:
978-3-319-40526-1=978-3-319-40528-5},
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.},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {511 - Computational Science and Mathematical Methods
(POF3-511) / ATMLPP - ATML Parallel Performance (ATMLPP)},
pid = {G:(DE-HGF)POF3-511 / G:(DE-Juel-1)ATMLPP},
typ = {PUB:(DE-HGF)7},
UT = {WOS:000411331500021},
doi = {10.1007/978-3-319-40528-5_21},
url = {https://juser.fz-juelich.de/record/820613},
}