Parameter estimation in the Hermitian and skew-Hermitian splitting method using gradient iterations

Abstract

This article presents enhancement strategies for the Hermitian and skew-Hermitian splitting method based on gradient iterations. The spectral properties are exploited for the parameter estimation, often resulting in a better convergence. In particular, steepest descent with early stopping can generate a rough estimate of the optimal upper bound. This is better than an arbitrary choice since the latter often causes stability problems or slow convergence. In addition, delayed gradient methods are considered as inner solvers for the splitting method. Experiments verify the effectiveness of the proposed estimation strategies and show that delayed gradient methods are competitive with conjugate gradient in low precision.