A heterogeneous CPU–GPU parallel approach to a multigrid Poisson solver for incompressible fluid simulation. (7th May 2013) - Jung, Hwi‐Ryong; Kim, Sun‐Tae; Noh, Junyong; Hong, Jeong‐Mo
ABSTRACT: One of the major obstacles in incompressible fluid simulations is the projection step that enforces zero divergence of the velocity field. We propose a novel heterogeneous CPU–GPU parallel multigrid Poisson solver that decomposes the high‐frequency components of the residual field using a wavelet decomposition and conducts an additional smoothing process on them, using the CPU, while the GPU is performing projection at the coarsest level. In example animations of smoke and turbulent flow with thermal buoyancy, this additional smoothing improves the accuracy of the parallel multigrid Poisson solver in a single multigrid cycle and reduces the number of multigrid cycles required to reach a specified accuracy. Copyright © 2013 John Wiley & Sons, Ltd. Abstract : We propose a novel heterogeneous CPU‐GPU parallel multigrid Poisson solver that decomposes the high‐frequency components of the residual field using a wavelet decomposition and conducts an additional smoothing on the CPU while the GPU handles the coarsest level evaluation. We demonstrate the efficiency of our solver with animations of smoke and turbulent flow with thermal buoyancy.