Accelerating the Conjugate Gradient Algorithm with GPUs in CFD Simulations
University of Tennessee, Innovative Computing Laboratory, Knoxville, USA
12th International Meeting on High Performance Computing for Computational Science, 2016
@article{anzt2016accelerating,
title={Accelerating the Conjugate Gradient Algorithm with GPUs in CFD Simulations},
author={Anzt, Hartwig and Baboulin, Marc and Dongarra, Jack and Fournier, Yvan and Hulsemann, Frank and Khabou, Amal and Wang, Yushan},
year={2016}
}
This paper illustrates how GPU computing can be used to accelerate computational fluid dynamics (CFD) simulations. For sparse linear systems arising from finite volume discretization, we evaluate and optimize the performance of Conjugate Gradient (CG) routines designed for manycore accelerators and compare against an industrial CPU-based implementation. We also investigate how the recent advances in preconditioning, such as iterative Incomplete Cholesky (IC, as symmetric case of ILU) preconditioning, match the requirements for solving real world problems.
July 18, 2016 by hgpu
