waLBerla

waLBerla (widely applicable Lattice Boltzmann from Erlangen) is a massively parallel framework for multi physics applications. Besides its original objective, Lattice Boltzmann solvers for hydrodynamics, it now contains modules for other applications like Multigrid and rigid body dynamics as well. Great emphasis is placed on the interoperability between the modules in particular the fluid-particle coupling. It scales from laptops to current and future supercomputers while maintaining near-perfect efficiency.

See https://www.walberla.net/ for more information and a showcase of applications.

Documentation and Tutorials

Documentation for the C++ framework is available in Doxygen, while the Python interface is documented in Sphinx.

Getting started

The minimum requirements are a C++17-compliant compiler (e.g. GCC or Clang) and the CMake build system. Furthermore, you need an MPI library (like Open MPI) if you want to make use of parallel processing capabilities. All of these dependencies are typically available in your operating system's package manager.

CMake

The typical steps, assuming your are in the waLBerla source directory, are:

• mkdir build; cd build create a build directory and change into it
• cmake .. call CMake with the waLBerla source directory as an argument
• make build waLBerla

To specify a CMake option you need to use -D(Option)=(Value). For example to set the C++ compiler one can use: cmake -DCMAKE_CXX_COMILER=clang++

To list and modify the CMake options the ccmake tool can be used. Just call ccmake . in your build directory to see and change the CMake options and variables.

Some important CMake variables:

• WALBERLA_BUILD_WITH_CODEGEN Enable pystencils code generation"
• Python_ROOT_DIR Specify the directory of the python executable. e.g. ~/miniconda/bin/
• MPI_HOME Specify the base directory of the MPI installation.
• WALBERLA_BUILD_WITH_PYTHON Support for embedding Python
• WALBERLA_BUILD_WITH_CUDA Enable CUDA support

For a full list of CMake Option see the CMakeLists.txt file or use ccmake as described above.

Codegen and Python

To use the lbmpy/pystencils code generation please install the packages with e.g. pip3 install lbmpy and specify the correct python environment when calling CMake.

In previous versions of CMake one could use PYTHON_EXECUTABLE or PYTHON_ROOT_DIR (all upper case) to specify the python executable or the directory. This does NOT work anymore. Please use Python_ROOT_DIR.

Get involved

Contributing

Please submit all code contributions on our GitLab. To get an account, please sign and submit the contributor license agreement.

Support

While we currently do not have a mailing list, any questions can be asked via the Issue Tracker.

Authors

Many thanks go to waLBerla's contributors

Please cite us

If you use waLBerla in a publication, please cite the following articles:

Overview:

• M. Bauer et al, waLBerla: A block-structured high-performance framework for multiphysics simulations. Computers & Mathematics with Applications, 2020. https://doi.org/10.1016/j.camwa.2020.01.007.

Grid Refinement:

• F. Schornbaum and U. Rüde, Massively parallel algorithms for the lattice boltzmann method on nonuniform grids. SIAM Journal on Scientific Computing, 2016. https://doi.org/10.1137/15M1035240

LBM - Particle Coupling:

• C. Rettinger and U. Rüde, A comparative study of fluid-particle coupling methods for fully resolved lattice Boltzmann simulations. Computers & Fluids, 2017. https://doi.org/10.1016/j.compfluid.2017.05.033

MESA-PD:

• S. Eibl and U. Rüde, A Modular and Extensible Software Architecture for Particle Dynamics. Proceedings Of The 8Th International Conference On Discrete Element Methods. https://mercurylab.co.uk/dem8/full-papers/#page-content

Carbon Nanotubes:

• G. Drozdov et al, Densification of single-walled carbon nanotube films: Mesoscopic distinct element method simulations and experimental validation. Journal of Applied Physics, 2020. https://doi.org/10.1063/5.0025505

License

waLBerla is licensed under GPLv3.