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@INPROCEEDINGS{Mateevitsi:1026000,
      author       = {Mateevitsi, Victor A. and Bode, Mathis and Ferrier, Nicola
                      and Fischer, Paul and Göbbert, Jens Henrik and Insley,
                      Joseph A. and Lan, Yu-Hsiang and Min, Misun and Papka,
                      Michael E. and Patel, Saumil and Rizzi, Silvio and
                      Windgassen, Jonathan},
      title        = {{S}caling {C}omputational {F}luid {D}ynamics: {I}n {S}itu
                      {V}isualization of {N}ek{RS} using {SENSEI}},
      address      = {New York, USA},
      publisher    = {Association for Computing Machinery},
      reportid     = {FZJ-2024-03256},
      isbn         = {9798400707858},
      pages        = {862–867},
      year         = {2023},
      comment      = {Proceedings of the SC '23 Workshops of The International
                      Conference on High Performance Computing, Network, Storage,
                      and Analysis - ACM New York, NY, USA, 2023},
      booktitle     = {Proceedings of the SC '23 Workshops of
                       The International Conference on High
                       Performance Computing, Network,
                       Storage, and Analysis - ACM New York,
                       NY, USA, 2023},
      abstract     = {In the realm of Computational Fluid Dynamics (CFD), the
                      demand for memory and computation resources is extreme,
                      necessitating the use of leadership-scale computing
                      platforms for practical domain sizes. This intensive
                      requirement renders traditional checkpointing methods
                      ineffective due to the significant slowdown in simulations
                      while saving state data to disk. As we progress towards
                      exascale and GPU-driven High-Performance Computing (HPC) and
                      confront larger problem sizes, the choice becomes
                      increasingly stark: to compromise data fidelity or to reduce
                      resolution. To navigate this challenge, this study advocates
                      for the use of in situ analysis and visualization
                      techniques. These allow more frequent data "snapshots" to be
                      taken directly from memory, thus avoiding the need for
                      disruptive checkpointing. We detail our approach of
                      instrumenting NekRS, a GPU-focused thermal-fluid simulation
                      code employing the spectral element method (SEM), and
                      describe varied in situ and in transit strategies for data
                      rendering. Additionally, we provide concrete scientific
                      use-cases and report on runs performed on Polaris, Argonne
                      Leadership Computing Facility’s (ALCF) 44 Petaflop
                      supercomputer and Jülich Wizard for European Leadership
                      Science (JUWELS) Booster, Jülich Supercomputing Centre’s
                      (JSC) 71 Petaflop High Performance Computing (HPC) system,
                      offering practical insight into the implications of our
                      methodology.},
      month         = {Nov},
      date          = {2023-11-12},
      organization  = {Workshops of The International
                       Conference on High Performance
                       Computing, Network, Storage, and
                       Analysis, Denver, CO (USA), 12 Nov 2023
                       - 17 Nov 2023},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / CoEC - Center of Excellence
                      in Combustion (952181)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(EU-Grant)952181},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      doi          = {10.1145/3624062.3624159},
      url          = {https://juser.fz-juelich.de/record/1026000},
}