Scaling WaterLily.jl with MPI and an improved geometric multigrid solver
For computational fluid dynamics practitioners, this work enables large-scale simulations on heterogeneous hardware with high parallel efficiency.
The paper presents MPI-based parallelism for WaterLily.jl, achieving near-ideal strong scaling and >96% weak-scaling efficiency up to 1 billion cells, alongside improvements to the geometric multigrid solver.
We present recent performance-oriented developments in WaterLily.jl, a scale-resolving incompressible flow solver written in pure Julia that runs seamlessly on CPUs and GPUs of any vendor. Supported by the newly added MPI-based parallelism, strong-scalability tests display a near-ideal linear trend, and weak-scaling efficiency is kept above 85\% before node memory-concurrency contention dominates parallel performance. Inter-node weak scalability is sustained above 96\% with grid size up to 1 billion cells. We further benchmark improvements to the geometric multigrid Poisson solver enabled by an adaptive under-relaxed red-black Gauss--Seidel smoother together with anisotropic coarsening operators.