Algorithm for Sparse Approximate Inverse Preconditioners in the Conjugate Gradient Method
A.A. Trofimuk Institute of Petroleum Geology and Geophysics SB RAS, 3, acad. Koptyug Ave., Novosibirsk 630090, Russia
Reliable Computing, Volume 19, 2013
@article{labutin2013algorithm,
title={Algorithm for Sparse Approximate Inverse Preconditioners in the Conjugate Gradient Method},
author={Labutin, Ilya B and Surodina, Irina V},
journal={Reliable Computing},
volume={19},
pages={121},
year={2013}
}
We propose a method for preconditioner construction and parallel implementations of the Preconditioned Conjugate Gradient algorithm on GPU platforms. The preconditioning matrix is an approximate inverse derived from an algorithm for the iterative improvement of a solution to linear equations. Using a sparse matrix-vector product, our preconditioner is well suited for massively parallel GPU architecture. We present numerical experiments and comparisons with CPU implementations.
December 9, 2013 by hgpu
