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@ARTICLE{Burstedde:857178,
      author       = {Burstedde, Carsten and Fonseca, Jose A. and Kollet, Stefan},
      title        = {{E}nhancing speed and scalability of the {P}ar{F}low
                      simulation code},
      journal      = {Computational geosciences},
      volume       = {22},
      number       = {1},
      issn         = {1573-1499},
      address      = {Bussum},
      publisher    = {Baltzer Science Publ.},
      reportid     = {FZJ-2018-06415},
      pages        = {347 - 361},
      year         = {2018},
      abstract     = {Regional hydrology studies are often supported by
                      high-resolution simulations of subsurface flow that require
                      expensive and extensive computations. Efficient usage of the
                      latest high performance parallel computing systems becomes a
                      necessity. The simulation software ParFlow has been
                      demonstrated to meet this requirement and shown to have
                      excellent solver scalability for up to 16,384 processes. In
                      the present work, we show that the code requires further
                      enhancements in order to fully take advantage of current
                      petascale machines. We identify ParFlow’s way of
                      parallelization of the computational mesh as a central
                      bottleneck. We propose to reorganize this subsystem using
                      fast mesh partition algorithms provided by the parallel
                      adaptive mesh refinement library p4est. We realize this in a
                      minimally invasive manner by modifying selected parts of the
                      code to reinterpret the existing mesh data structures. We
                      evaluate the scaling performance of the modified version of
                      ParFlow, demonstrating good weak and strong scaling up to
                      458k cores of the Juqueen supercomputer, and test an example
                      application at large scale.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000423708300020},
      doi          = {10.1007/s10596-017-9696-2},
      url          = {https://juser.fz-juelich.de/record/857178},
}