waLBerla: A block-structured high-performance framework for multiphysics simulations

September 30, 2019 Β· Declared Dead Β· πŸ› Computers and Mathematics with Applications

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Authors Martin Bauer, Sebastian Eibl, Christian Godenschwager, Nils Kohl, Michael Kuron, Christoph Rettinger, Florian Schornbaum, Christoph Schwarzmeier, Dominik ThΓΆnnes, Harald KΓΆstler, Ulrich RΓΌde arXiv ID 1909.13772 Category cs.DC: Distributed Computing Cross-listed cs.CE, physics.comp-ph Citations 102 Venue Computers and Mathematics with Applications Last Checked 4 months ago
Abstract
Programming current supercomputers efficiently is a challenging task. Multiple levels of parallelism on the core, on the compute node, and between nodes need to be exploited to make full use of the system. Heterogeneous hardware architectures with accelerators further complicate the development process. waLBerla addresses these challenges by providing the user with highly efficient building blocks for developing simulations on block-structured grids. The block-structured domain partitioning is flexible enough to handle complex geometries, while the structured grid within each block allows for highly efficient implementations of stencil-based algorithms. We present several example applications realized with waLBerla, ranging from lattice Boltzmann methods to rigid particle simulations. Most importantly, these methods can be coupled together, enabling multiphysics simulations. The framework uses meta-programming techniques to generate highly efficient code for CPUs and GPUs from a symbolic method formulation. To ensure software quality and performance portability, a continuous integration toolchain automatically runs an extensive test suite encompassing multiple compilers, hardware architectures, and software configurations.
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