waLBerla - Widely applicable Lattice Boltzmann from Erlangen

Internally funded project

Project Details

Project leader:
Prof. Dr. Ulrich Rüde
Prof. Dr. Harald Köstler

Project members:
Regina Degenhardt
Martin Bauer
Dominik Bartuschat
Kristina Pickl
Florian Schornbaum
Simon Bogner
Christian Godenschwager
Christoph Rettinger
Christoph Schwarzmeier
Sebastian Eibl
Jan Hönig

Contributing FAU Organisations:
Lehrstuhl für Informatik 10 (Systemsimulation)
Technische Fakultät

Acronym: waLBerla
Start date: 01/01/2007
End date: 01/01/2099

Abstract (technical / expert description):

Solving problems in present-day simulation is becoming more and more complex. Both the number of physical effects taken into account and the complexity of the associated software development process increase. In order to meet these growing demands, the Chair for System Simulation (LSS) developed the massively parallel and flexible simulation framework waLBerla (widely applicable Lattice Boltzmann solver from Erlangen). Originally, the framework has been centered around the Lattice-Boltzmann method for the simulation of fluid scenarios. Meanwhile, its usability is not only limited to this algorithm but it is also suitable for a wide range of applications, based on structured grids. For example, an efficient multigrid solver for partial differential equations has been integrated. Next to the basic requirements of easy adaptivity and extensibility for new fluid problems, the waLBerla project also aims at physical correctness and high performance. A particular feature is the simulation of large ensembles of geometrically fully resolved, and arbitrarily shaped particles within fluid flows. Even on 294912 cores, it is possible to gain an efficieny of more than 95%. Hence, waLBerla is a comprehensive program rich in features as well as a library for the easy development of new applications based on fluid simulation. Thus, it meets the requirements of scientific researchers, performance optimizers, code developers as well as for industrial cooperations.

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Rettinger, C., & Rüde, U. (2019). Dynamic Load Balancing Techniques for Particulate Flow Simulations. Computation, 7(1). https://dx.doi.org/10.3390/computation7010009
Schwarzmeier, C., & Rüde, U. (2019, February). Simulating coupled free and porous media flow with lattice Boltzmann methods. Paper presentation at 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics, Wien, AT.
Rettinger, C. (2019). waLBerla: A General Purpose Software Framework for Massively Parallel Simulations. Paper presentation at SIAM Conference on Computational Science and Engineering, Spokane, US.
Rettinger, C., & Rüde, U. (2018). A coupled lattice Boltzmann method and discrete element method for discrete particle simulations of particulate flows. Computers & Fluids, 706-719. https://dx.doi.org/10.1016/j.compfluid.2018.01.023
Rettinger, C. (2018). Adaptive Grid Refinement Techniques for Particulate Flow Simulations with the Lattice Boltzmann Method. Poster presentation at Platform for Advanced Scientific Computing (PASC) Conference, Basel, CH.
Rettinger, C. (2018). Adaptive Mesh Refinement and Load Balancing Techniques for Particulate Flow Simulations. Poster presentation at CoSaS - International Symposium on Computational Science at Scale, Erlangen, DE.
Rüde, U., & Bauer, M. (2018). An improved lattice Boltzmann D3Q19 method based on an alternative equilibrium discretization. arXiv. https://dx.doi.org/10.1016/j.camwa.2010.03.022
Bartuschat, D., & Rüde, U. (2018). A scalable multiphysics algorithm for massively parallel direct numerical simulations of electrophoresis. Journal of Computational Science, 27, 147 - 167. https://dx.doi.org/10.1016/j.jocs.2018.05.011
Schornbaum, F. (2018). Block-Structured Adaptive Mesh Refinement for Simulations on Extreme-Scale Supercomputers (Dissertation).
Schornbaum, F., & Rüde, U. (2018). Extreme-Scale Block-Structured Adaptive Mesh Refinement. SIAM Journal on Scientific Computing. https://dx.doi.org/10.1137/17M1128411

Last updated on 2019-16-04 at 11:47