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

TL;DR

waLBerla is a high-performance, flexible framework that enables efficient multiphysics simulations on modern supercomputers by leveraging block-structured grids, meta-programming, and automated testing across diverse hardware.

Contribution

It introduces a versatile framework with efficient building blocks for multiphysics simulations on block-structured grids, supporting heterogeneous hardware and automated performance optimization.

Findings

Supports complex geometries with flexible domain partitioning

Enables efficient stencil-based algorithms on structured grids

Facilitates coupled multiphysics simulations with high performance

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.