Development of a Restricted Additive Schwarz Preconditioner for Sparse Linear Systems on NVIDIA GPU
Department of Chemical and Petroleum Engineering, University of Calgary, Calgary, AB, Canada, T2N 1N4
International Journal of Numerical Analysis and Modeling, Series B, Volume 5, Number 1-2, Pages 13-20, 2014
@article{liu2014development,
title={Development of a Restricted Additive Schwarz Preconditioner for Sparse Linear Systems on NVIDIA GPU},
author={Liu, Hui and Chen, Zhangxin and Yu, Song and Hsieh, Ben and Shao, Lei},
year={2014}
}
In this paper, we develop, study and implement a restricted additive Schwarz (RAS) preconditioner for speedup of the solution of sparse linear systems on NVIDIA Tesla GPU. A novel algorithm for constructing this preconditioner is proposed. This algorithm involves two phases. In the first phase, the construction of the RAS preconditioner is transformed to an incomplete-LU problem. In the second phase, a parallel triangular solver is developed and the incomplete-LU problem is solved by this solver. Numerical experiments show that the speedup of this preconditioner is sufficiently high.
July 11, 2014 by hgpu
