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@INBOOK{Wolf:820614,
      author       = {Wolf, Felix and Bischof, Christian and Calotoiu, Alexandru
                      and Hoefler, Torsten and Iwainsky, Christian and
                      Kwasniewski, Grzegorz and Mohr, Bernd and Shudler, Sergei
                      and Strube, Alexandre and Vogel, Andreas and Wittum,
                      Gabriel},
      title        = {{A}utomatic {P}erformance {M}odeling of {HPC}
                      {A}pplications},
      volume       = {113},
      address      = {Cham, Switzerland},
      publisher    = {Springer International Publishing},
      reportid     = {FZJ-2016-05886},
      isbn         = {978-3-319-40526-1},
      series       = {Lecture Notes in Computational Science and Engineering},
      pages        = {445 - 465},
      year         = {2016},
      comment      = {Software for Exascale Computing - SPPEXA 2013-2015 /
                      Bungartz, Hans-Joachim (Editor) ; Chapter 20 ; ISBN:
                      978-3-319-40526-1=978-3-319-40528-5},
      booktitle     = {Software for Exascale Computing -
                       SPPEXA 2013-2015 / Bungartz,
                       Hans-Joachim (Editor) ; Chapter 20 ;
                       ISBN:
                       978-3-319-40526-1=978-3-319-40528-5},
      abstract     = {Many existing applications suffer from inherent scalability
                      limitations that will prevent them from running at exascale.
                      Current tuning practices, which rely on diagnostic
                      experiments, have drawbacks because (i) they detect
                      scalability problems relatively late in the development
                      process when major effort has already been invested into an
                      inadequate solution and (ii) they incur the extra cost of
                      potentially numerous full-scale experiments. Analytical
                      performance models, in contrast, allow application
                      developers to address performance issues already during the
                      design or prototyping phase. Unfortunately, the difficulties
                      of creating such models combined with the lack of
                      appropriate tool support still render performance modeling
                      an esoteric discipline mastered only by a relatively small
                      community of experts. This article summarizes the results of
                      the Catwalk project, which aimed to create tools that
                      automate key activities of the performance modeling process,
                      making this powerful methodology accessible to a wider
                      audience of HPC application developers.},
      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:000411331500020},
      doi          = {10.1007/978-3-319-40528-5_20},
      url          = {https://juser.fz-juelich.de/record/820614},
}