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Advances in Computational Process Engineering using Lattice Boltzmann Methods on High Performance Computers

In: High Performance Computing in Science and Engineering '22

Author

Listed:
  • Adrian Kummerländer

    (Karlsruhe Institute of Technology (KIT), Institute of Applied and Numerical Mathematics (IANM), Lattice Boltzmann Research Group (LBRG))

  • Fedor Bukreev

    (Karlsruhe Institute of Technology (KIT), Institute of Mechanical Process Engineering and Mechanics (MVM), Lattice Boltzmann Research Group (LBRG))

  • Simon F. R. Berg

    (Karlsruhe Institute of Technology (KIT), Institute of Mechanical Process Engineering and Mechanics (MVM), Lattice Boltzmann Research Group (LBRG))

  • Marcio Dorn

    (Universidade Federal do Rio Grande do Sul (UFRGS), Institute of Informatics (INF))

  • Mathias J. Krause

    (Karlsruhe Institute of Technology (KIT), Institute of Applied and Numerical Mathematics (IANM), Lattice Boltzmann Research Group (LBRG)
    Karlsruhe Institute of Technology (KIT), Institute of Mechanical Process Engineering and Mechanics (MVM), Lattice Boltzmann Research Group (LBRG))

Abstract

The present annual report documents the parallelization benefits of Lattice-Boltzmann particulate multiphase flow simulations realized in the open source software library OpenLB and performed on the HoreKa supercomputer. For this purpose, the parallel efficiency and total performance of test cases utilizing vectorization on CPUs as well as GPUs is evaluated for simulations up to 10 billion cells and node counts up to 320 CPU resp. 56 GPU nodes. Selected applications of these capabilities to resolved turbulent large eddy multiphase simulations conducted using Eulerian and Lagrangian approaches are described.

Suggested Citation

  • Adrian Kummerländer & Fedor Bukreev & Simon F. R. Berg & Marcio Dorn & Mathias J. Krause, 2024. "Advances in Computational Process Engineering using Lattice Boltzmann Methods on High Performance Computers," Springer Books, in: Wolfgang E. Nagel & Dietmar H. Kröner & Michael M. Resch (ed.), High Performance Computing in Science and Engineering '22, pages 233-247, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-46870-4_16
    DOI: 10.1007/978-3-031-46870-4_16
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