Parallel algorithms for dynamically partitioning unstructured grids

Three algorithms suitable for parallel dynamic load-balancing which attempt to partition unstructured grids so that computational load is balanced and communication is minimized are described.

Abstract

Grid partitioning is the method of choice for decomposing a wide variety of computational problems into naturally parallel pieces. In problems where computational load on the grid or the grid itself changes as the simulation progresses, the ability to repartition dynamically and in parallel is attractive for achieving higher performance. We describe three algorithms suitable for parallel dynamic load-balancing which attempt to partition unstructured grids so that computational load is balanced and communication is minimized. The execution time of algorithms and the quality of the partitions they generate are compared to results from serial partitioners for two large grids. The integration of the algorithms into a parallel particle simulation is also briefly discussed.