Abstract
AbstractWe 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.
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