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@INPROCEEDINGS{Badwaik:1030182,
      author       = {Badwaik, Jayesh and Herten, Andreas and Veneva, Milena},
      title        = {{O}ptimizing an {LBM} {A}pplication {U}sing {CUDA}
                      {G}raphs},
      reportid     = {FZJ-2024-05240},
      year         = {2023},
      abstract     = {With increasing focus on scalability and performance of
                      high performance computing applications, it has become
                      important for the simulation softwares to be able to utilize
                      the underlying hardware as comprehensively to its maximum
                      performance. waLBerla is a multiphysics software framework
                      that has achieved high scalability and performance. It
                      achieves this excellent performance due to architecture
                      specific code generation algorithms combined with efficient
                      communication and parallel data structures like BlockForest.
                      In this work, we attempt to improve the GPU utilization of
                      an Lattice-Boltzmann Method (LBM) software.},
      month         = {May},
      date          = {2023-05-22},
      organization  = {ISC High Performance 2023, Hamburg
                       (Germany), 22 May 2023 - 25 May 2023},
      subtyp        = {Other},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / SCALABLE - SCAlable LAttice
                      Boltzmann Leaps to Exascale (956000) / ATML-X-DEV - ATML
                      Accelerating Devices (ATML-X-DEV)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(EU-Grant)956000 /
                      G:(DE-Juel-1)ATML-X-DEV},
      typ          = {PUB:(DE-HGF)24},
      doi          = {10.34734/FZJ-2024-05240},
      url          = {https://juser.fz-juelich.de/record/1030182},
}