waLBerla: Optimization for itanium-based systems with thousands of processors. Performance optimization is an issue at different levels, in particular for computing and communication intensive codes like free surface lattice Boltzmann. This method is used to simulate liquid-gas flow phenomena such as bubbly flows and foams. Due to a special treatment of the gas phase, an aggregation of bubble volume data is necessary in every time step. In order to accomplish efficient parallel scaling, the all-to-all communication schemes used up to now had to be replaced with more sophisticated patterns that work in a local vicinity. With this approach, scaling could be improved such that simulation runs on up to 9 152 processor cores are possible with more than 90

References in zbMATH (referenced in 18 articles , 1 standard article )

Showing results 1 to 18 of 18.
Sorted by year (citations)

  1. Montessori, A.; Lauricella, M.; Succi, S.: Mesoscale modelling of soft flowing crystals (2019)
  2. Weinzierl, Tobias: The Peano software -- parallel, automaton-based, dynamically adaptive grid traversals (2019)
  3. Wittmann, M.; Haag, V.; Zeiser, T.; Köstler, H.; Wellein, G.: Lattice Boltzmann benchmark kernels as a testbed for performance analysis (2018)
  4. Bartuschat, Dominik; Fischermeier, Ellen; Gustavsson, Katarina; Rüde, Ulrich: Two computational models for simulating the tumbling motion of elongated particles in fluids (2016)
  5. Fattahi, Ehsan; Waluga, Christian; Wohlmuth, Barbara; Rüde, Ulrich: Large scale lattice Boltzmann simulation for the coupling of free and porous media flow (2016)
  6. Fattahi, Ehsan; Waluga, Christian; Wohlmuth, Barbara; Rüde, Ulrich; Manhart, Michael; Helmig, Rainer: Lattice Boltzmann methods in porous media simulations: from laminar to turbulent flow (2016)
  7. Schornbaum, Florian; Rüde, Ulrich: Massively parallel algorithms for the lattice Boltzmann method on nonuniform grids (2016)
  8. Bogner, Simon; Ammer, Regina; Rüde, Ulrich: Boundary conditions for free interfaces with the lattice Boltzmann method (2015)
  9. Ammer, Regina; Markl, Matthias; Ljungblad, Ulric; Körner, Carolin; Rüde, Ulrich: Simulating fast electron beam melting with a parallel thermal free surface lattice Boltzmann method (2014)
  10. Neumann, Philipp; Eckhardt, Wolfgang; Bungartz, Hans-Joachim: Hybrid molecular-continuum methods: from prototypes to coupling software (2014)
  11. Habich, J.; Feichtinger, C.; Köstler, H.; Hager, G.; Wellein, G.: Performance engineering for the lattice Boltzmann method on GPGPUs: architectural requirements and performance results (2013) ioport
  12. Neumann, Philipp; Neckel, Tobias: A dynamic mesh refinement technique for lattice Boltzmann simulations on octree-like grids (2013)
  13. Wittmann, M.; Zeiser, T.; Hager, G.; Wellein, G.: Domain decomposition and locality optimization for large-scale lattice Boltzmann simulations (2013)
  14. Donath, Stefan; Mecke, Klaus; Rabha, Swapna; Buwa, Vivek; Rüde, Ulrich: Verification of surface tension in the parallel free surface lattice Boltzmann method in waLBerla (2011)
  15. Feichtinger, Christian; Habich, Johannes; Köstler, Harald; Hager, Georg; Rüde, Ulrich; Wellein, Gerhard: A flexible patch-based lattice Boltzmann parallelization approach for heterogeneous GPU-CPU clusters (2011) ioport
  16. Masilamani, Kannan; Ganguly, Suvankar; Feichtinger, Christian; Rüde, Ulrich: Hybrid lattice-Boltzmann and finite-difference simulation of electroosmotic flow in a microchannel (2011)
  17. Donath, S.; Götz, J.; Feichtinger, C.; Igiberger, K.; Rüde, U.: waLBerla: Optimization for itanium-based systems with thousands of processors (2010)
  18. Götz, J.; Iglberger, K.; Feichtinger, C.; Donath, S.; Rüde, U.: Coupling multibody dynamics and computational fluid dynamics on 8192 processor cores (2010)