A Class of Incomplete Orthogonal Factorization Methods. II: Implementation and Results
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We present, implement and test several incomplete QR factorization methods based on Givens rotations for sparse square and rectangular matrices. For square systems, the approximate QR factors are used as right-preconditioners for GMRES, and their performance is compared to standard ILU techniques. For rectangular matrices corresponding to linear least-squares problems, the approximate R factor is used as a right-preconditioner for CGLS. A comprehensive discussion is given about the uses, advantages and shortcomings of the preconditioners.
AMS subject classification (2000)
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- A Class of Incomplete Orthogonal Factorization Methods. II: Implementation and Results
BIT Numerical Mathematics
Volume 45, Issue 1 , pp 159-179
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- sparse linear systems
- sparse least-squares
- iterative methods
- incomplete orthogonal factorizations
- Givens rotations
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