Parallel preconditioners for the conjugate gradient algorithm using GramSchmidt and least squares methods
This paper is devoted to the study of some preconditioned conjugate gradient algorithms on parallel computers. The considered preconditioners (presented in [J. Straubhaar, Preconditioners for the conjugate gradient algorithm using GramSchmidt and least squares methods, Int. J. Comput. Math. 84 (1) (2007) 89108]) are based on incomplete GramSchmidt orthogonalization and least squares methods. The construction of the preconditioner and the resolution are treated separately. Numerical tests are performed and speed-up curves are presented in order to evaluate the performance of the algorithms.
parallelization least squares gramschmidt orthogonalization performance speed-up preconditioned conjugate gradient method