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@MASTERSTHESIS{Frings:26050,
      author       = {Frings, W.},
      title        = {{S}trategien zur {K}opplung und {D}atenreduktion bei der
                      {O}nline-{V}isualisierung von parallelen
                      {S}imulationsrechnungen mit verteilter {D}atenhaltung},
      volume       = {4021},
      issn         = {0944-2952},
      type         = {Diplom (FH)},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {PreJuSER-26050, Juel-4021},
      series       = {Berichte des Forschungszentrums Jülich},
      pages        = {VIII, 114 S.},
      year         = {2002},
      note         = {Record converted from VDB: 12.11.2012; 2002},
      abstract     = {Visualizing data just being calculated by a simulation
                      program running an a remote computer is called online
                      visualization. This method allows an immediate visualization
                      and a direct control of simulation parameters (computational
                      steering). Applying online visualization to large-scale
                      applications an parallel supercomputers with distributed
                      memory lead to two major problems: an one hand the huge
                      amount of data which have to be transfered between
                      simulation and visualization and an the other hand the
                      distributed data management within the simulation program.
                      The first Problem is tackled by a compression procedure an
                      the basis of a wavelet transformation which is implemented
                      in this thesis. This allows to decompose the data in
                      different resolution steps and to transfer them
                      progressively to the visualization. To overcome the second
                      problem coupling strategies for the distributed data
                      management are introduced, which take into account the
                      parallel structure of the simulation program and ensure a
                      reliable transfer of the decomposed data located an the
                      single processors. The benchmarking of the applied
                      compression techniques and coupling strategies with respect
                      to the run time behavior and to the effects an a parallel
                      simulation program was done by simplified models and
                      validated by real time measurements. For that purpose a
                      library $\textit{LVISIT}$ and a code generator
                      $\textit{visitcg}$ were developed, which use the
                      communication library $\textit{VISIT}$ and provide the
                      coupling techniques introduced here together with a
                      compression based an wavelet transformation.},
      cin          = {ZAM},
      cid          = {I:(DE-Juel1)VDB62},
      pnm          = {Betrieb und Weiterentwicklung des Höchstleistungsrechners},
      pid          = {G:(DE-Juel1)FUEK254},
      typ          = {PUB:(DE-HGF)10},
      url          = {https://juser.fz-juelich.de/record/26050},
}