A robust incomplete factorization preconditioner for positive definite matrices

Abstract We describe a novel technique for computing a sparse incomplete factorization of a general symmetric positive definite matrix A . The factorization is not based on the Cholesky algorithm (or Gaussian elimination), but on A ‐orthogonalization. Thus, the incomplete factorization always exists and can be computed without any diagonal modification. When used in conjunction with the conjugate gradient algorithm, the new preconditioner results in a reliable solver for highly ill‐conditioned linear systems. Comparisons with other incomplete factorization techniques using challenging linear systems from structural analysis and solid mechanics problems are presented. Copyright © 2003 John Wiley & Sons, Ltd.