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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},
}