AMRaCut: Scalable Partitioning for Adaptive Mesh Refinement

Mesh partitioning is critical for scalable distributed PDE solvers. Traditional methods like spatial ordering and multi-level graph partitioning have significant tradeoffs between partition quality and parallel scalability. We present AMRaCut, a distributed-parallel mesh partitioner that bridges this gap using parallel label propagation and graph diffusion. It operates mostly locally on initial partitions, limiting inter-process communications to neighboring processes. This locality is especially effective in AMR, where mesh evolves dynamically with mostly local changes.