A Geometric Multigrid Solver on GPU Clusters

Recently, more and more GPU HPC clusters are installed and thus there is a need to adapt existing software design concepts to multi-GPU environments. We have developed a modular and easily extensible software framework called WaLBerla that covers a wide range of applications ranging from particulate flows over free surface flows to nano fluids coupled with temperature simulations. In this article we report on our experiences to extend WaLBerla in order to support geometric multigrid algorithms for the numerical solution of partial differential equations (PDEs) on multi-GPU clusters. We discuss the object-oriented software and performance engineering concepts necessary to integrate efficient compute kernels into our WaLBerla framework and show that a large fraction of the high computational performance offered by current heterogeneous HPC clusters can be sustained for geometric multigrid algorithms.