Symmetric Permutations for I-matrices to Delay and Avoid Small Pivots During Factorization
نویسنده
چکیده
In this article, we present several new permutations for I-matrices making these more suitable for incomplete LDU-factorization preconditioners used in solving linear systems by iterative methods. A general matrix can be transformed by row permutation as well as row and columns scaling into an I-matrix, i.e. a matrix having elements of modulus 1 on the diagonal and elements of modulus of no more than 1 elsewhere. Reordering rows and columns by the same permutation clearly preserves I-matrices. In this article, we consider such reordering techniques which make the permuted matrix more suitable for an incomplete LDU-factorization preconditioner than the original I-matrix. We use a multilevel ILUC, an incomplete LDU-factorization preconditioner using Crout’s implementation of Gaussian elimination without pivoting to test these reorderings. The combination of I-matrix preprocessing with the various algorithms presented here and the multilevel incomplete LDU-factorizations forms a powerful preconditioning method for unsymmetric, highly indefinite problems.
منابع مشابه
Stability of Block LDLT Factorization of a Symmetric Tridiagonal Matrix
For symmetric indeenite tridiagonal matrices, block LDL T factorization without interchanges is shown to have excellent numerical stability when a pivoting strategy of Bunch is used to choose the dimension (1 or 2) of the pivots.
متن کاملExperimental Study of ILU Preconditioners for Indefinite Matrices
Incomplete LU factorization preconditioners have been surprisingly successful for many cases of general nonsymmetric and indeenite matrices. However, their failure rate is still too high for them to be useful as black-box library software for general matrices. Besides fatal breakdowns due to zero pivots, the major causes of failure are inaccuracy, and instability of the triangular solves. When ...
متن کاملCompressed threshold pivoting for sparse symmetric indefinite systems
A key technique for controlling numerical stability in sparse direct solvers is threshold partial pivoting. When selecting a pivot, the entire candidate pivot column below the diagonal must be up-to-date and must be scanned. If the factorization is parallelized across a large number of cores, communication latencies can be the dominant computational cost. In this paper, we propose two alternati...
متن کاملStability of block LDL factorization of a symmetric tridiagonal matrix
For symmetric inde®nite tridiagonal matrices, block LDL factorization without interchanges is shown to have excellent numerical stability when a pivoting strategy of Bunch is used to choose the dimension (1 or 2) of the pivots. Ó 1999 Elsevier Science Inc. All rights reserved. AMS classi®cation: 65F05; 65G05
متن کاملNew Pivot Selection for Sparse Symmetric Indefinite Factorization
We propose a new pivot selection technique for symmetric indefinite factorization of sparse matrices. Such factorization should maintain both sparsity and numerical stability of the factors, both of which depend solely on the choices of the pivots. Our method is based on the minimum degree algorithm and also considers the stability of the factors at the same time. Our experiments show that our ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- SIAM J. Scientific Computing
دوره 30 شماره
صفحات -
تاریخ انتشار 2008