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ACM Trans Math Softw. 2014 Feb;40(2). doi: 10.1145/2527267.

Algorithm 937: MINRES-QLP for Symmetric and Hermitian Linear Equations and Least-Squares Problems.

Author information

1
University of Chicago/Argonne National Laboratory.
2
Stanford University.

Abstract

We describe algorithm MINRES-QLP and its FORTRAN 90 implementation for solving symmetric or Hermitian linear systems or least-squares problems. If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential instability in the original MINRES algorithm. A positive-definite pre-conditioner may be supplied. Our FORTRAN 90 implementation illustrates a design pattern that allows users to make problem data known to the solver but hidden and secure from other program units. In particular, we circumvent the need for reverse communication. Example test programs input and solve real or complex problems specified in Matrix Market format. While we focus here on a FORTRAN 90 implementation, we also provide and maintain MATLAB versions of MINRES and MINRES-QLP.

KEYWORDS:

Algorithms; Krylov subspace method; Lanczos process; conjugate-gradient method; data encapsulation; ill-posed problem; linear equations; minimum-residual method; pseudoinverse solution; regression; singular least-squares; sparse matrix

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