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@ARTICLE{Geimer:9826,
      author       = {Geimer, M. and Wolf, F. and Wylie, B. and Ábrahám, E. and
                      Becker, D. and Mohr, B.},
      title        = {{T}he {S}calasca performance toolset architecture},
      journal      = {Concurrency and computation},
      volume       = {22},
      issn         = {1532-0626},
      address      = {Chichester},
      publisher    = {Wiley},
      reportid     = {PreJuSER-9826},
      pages        = {702 - 719},
      year         = {2010},
      note         = {Contract/grant sponsor: Helmholtz Association;
                      contract/grant numbers: VH-NG-118, VH-VI-228Contract/grant
                      sponsor: German Federal Ministry of Research and Education
                      (BMBF); contract/grant number: 01IS07005C},
      abstract     = {Scalasca is a performance toolset that has been
                      specifically designed to analyze parallel application
                      execution behavior on large-scale systems with many
                      thousands of processors. It offers an incremental
                      performance-analysis procedure that integrates runtime
                      summaries with in-depth studies of concurrent behavior via
                      event tracing, adopting a strategy of successively refined
                      measurement configurations. Distinctive features are its
                      ability to identify wait states in applications with very
                      large numbers of processes and to combine these with
                      efficiently summarized local measurements. In this article,
                      we review the current toolset architecture, emphasizing its
                      scalable design and the role of the different components in
                      transforming raw measurement data into knowledge of
                      application execution behavior. The scalability and
                      effectiveness of Scalasca are then surveyed from experience
                      measuring and analyzing real-world applications on a range
                      of computer systems. Copyright (C) 2010 John Wiley $\&$
                      Sons, Ltd.},
      keywords     = {J (WoSType)},
      cin          = {JSC / JARA-HPC},
      ddc          = {004},
      cid          = {I:(DE-Juel1)JSC-20090406 / $I:(DE-82)080012_20140620$},
      pnm          = {Scientific Computing (FUEK411) / 411 - Computational
                      Science and Mathematical Methods (POF2-411) / ATMLPP - ATML
                      Parallel Performance (ATMLPP)},
      pid          = {G:(DE-Juel1)FUEK411 / G:(DE-HGF)POF2-411 /
                      G:(DE-Juel-1)ATMLPP},
      shelfmark    = {Computer Science, Software Engineering / Computer Science,
                      Theory $\&$ Methods},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000276682000003},
      doi          = {10.1002/cpe.1556},
      url          = {https://juser.fz-juelich.de/record/9826},
}