Quantum mechanics

Computational science

Multiphysics

Implementation

Stencil

CUDA

Compiler

Parallel computing

Computer science

Grid

Distributed computing

Software portability

Software

Thermodynamics

Physics

Finite element method

Mathematics

Component-based software engineering

Supercomputer

Toolchain

Computer engineering

Block (permutation group theory)

Geometry

Software framework

Programming language

Python (programming language)

Lattice Boltzmann methods

Software development

Computers & Mathematics with Applications

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.

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