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@INPROCEEDINGS{Vierjahn:824330,
      author       = {Vierjahn, Tom and Hermanns, Marc-André and Mohr, Bernd and
                      Müller, Matthias S. and Kuhlen, Torsten W. and Hentschel,
                      Bernd},
      title        = {{U}sing {D}irected {V}ariance to {I}dentify {M}eaningful
                      {V}iews in {C}all-path {P}erformance {P}rofiles},
      address      = {Piscataway, NJ, USA},
      publisher    = {IEEE Press},
      reportid     = {FZJ-2016-06939},
      isbn         = {978-1-5090-5226-4},
      pages        = {9-16},
      year         = {2016},
      comment      = {Proceedings of the 3rd International Workshop on Visual
                      Performance Analysis},
      booktitle     = {Proceedings of the 3rd International
                       Workshop on Visual Performance
                       Analysis},
      abstract     = {Understanding the performance behaviour of massively
                      parallel high-performance computing (HPC) applications based
                      on call-path performance profiles is a time-consuming task.
                      In this paper, we introduce the concept of directed variance
                      in order to help analysts find performance bottlenecks in
                      massive performance data and in the end optimize the
                      application. According to HPC experts' requirements, our
                      technique automatically detects severe parts in the data
                      that expose large variation in an application's performance
                      behaviour across system resources. Previously known
                      variations are effectively filtered out. Analysts are thus
                      guided through a reduced search space towards regions of
                      interest for detailed examination in a 3D visualization. We
                      demonstrate the effectiveness of our approach using
                      performance data of common benchmark codes as well as from
                      actively developed production codes.},
      month         = {Nov},
      date          = {2016-11-18},
      organization  = {The 3rd International Workshop on
                       Visual Performance Analysis, Salt Lake
                       City, Utah (USA), 18 Nov 2016 - 18 Nov
                       2016},
      cin          = {JSC / JARA-HPC},
      cid          = {I:(DE-Juel1)JSC-20090406 / $I:(DE-82)080012_20140620$},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / Scalable Performance Analysis of Large-Scale
                      Parallel Applications $(jzam11_20091101)$ / ATMLPP - ATML
                      Parallel Performance (ATMLPP)},
      pid          = {G:(DE-HGF)POF3-511 / $G:(DE-Juel1)jzam11_20091101$ /
                      G:(DE-Juel-1)ATMLPP},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      doi          = {10.1109/vpa.2016.7},
      url          = {https://juser.fz-juelich.de/record/824330},
}