Parallel Multigrid Acceleration for the Finite-Element Gaussian Belief Propagation Algorithm

摘要

We introduce a novel parallel multigrid algorithm, referred to as the finite-element multigrid Gaussian belief propagation (FMGaBP), to accelerate the convergence of the recently introduced finite-element Gaussian belief propagation solver. The FMGaBP algorithm processes the FEM computation in a fully distributed and parallel manner, with stencil-like element-by-element operations, demonstrating high parallel efficiency. The results for both sequential as well as parallel message scheduling versions of FMGaBP demonstrate high convergence rates independent of the scale of discretization on the finest mesh. In comparison with the multigrid preconditioned conjugate gradient (MG-PCG) solver, the FMGaBP algorithm demonstrates considerable iteration reductions as tested by Laplace benchmark problems. In addition, the parallel implementation of FMGaBP shows a speedup of 2.9 times over the parallel implementation of MG-PCG using eight CPU cores.