Data type in double but solving problem using single precision routines for general (i.e., unsymmetric, in some cases rectangular) matrix
- dsgesv : Solves a general system of linear equations AX=B using iterativement refinement.
dsgesv
Solves a general system of linear equations AX=B using iterativement refinement.
USAGE:
ipiv, x, iter, info, a = NumRu::Lapack.dsgesv( a, b)
or
NumRu::Lapack.dsgesv # print help
FORTRAN MANUAL
SUBROUTINE DSGESV( N, NRHS, A, LDA, IPIV, B, LDB, X, LDX, WORK, SWORK, ITER, INFO)
* Purpose
* =======
*
* DSGESV computes the solution to a real system of linear equations
* A * X = B,
* where A is an N-by-N matrix and X and B are N-by-NRHS matrices.
*
* DSGESV first attempts to factorize the matrix in SINGLE PRECISION
* and use this factorization within an iterative refinement procedure to
* produce a solution with DOUBLE PRECISION normwise backward error
* quality (see below). If the approach fails the method switches to a
* DOUBLE PRECISION factorization and solve.
*
* The iterative refinement is not going to be a winning strategy if
* the ratio SINGLE PRECISION performance over DOUBLE PRECISION performance
* is too small. A reasonable strategy should take the number of right-hand
* sides and the size of the matrix into account. This might be done with a
* call to ILAENV in the future. Up to now, we always try iterative refinement.
*
* The iterative refinement process is stopped if
* ITER > ITERMAX
* or for all the RHS we have:
* RNRM < SQRT(N)*XNRM*ANRM*EPS*BWDMAX
* where
* o ITER is the number of the current iteration in the iterative
* refinement process
* o RNRM is the infinity-norm of the residual
* o XNRM is the infinity-norm of the solution
* o ANRM is the infinity-operator-norm of the matrix A
* o EPS is the machine epsilon returned by DLAMCH('Epsilon')
* The value ITERMAX and BWDMAX are fixed to 30 and 1.0D+00 respectively.
*
* Arguments
* =========
*
* N (input) INTEGER
* The number of linear equations, i.e., the order of the
* matrix A. N >= 0.
*
* NRHS (input) INTEGER
* The number of right hand sides, i.e., the number of columns
* of the matrix B. NRHS >= 0.
*
* A (input or input/ouptut) DOUBLE PRECISION array,
* dimension (LDA,N)
* On entry, the N-by-N coefficient matrix A.
* On exit, if iterative refinement has been successfully used
* (INFO.EQ.0 and ITER.GE.0, see description below), then A is
* unchanged, if double precision factorization has been used
* (INFO.EQ.0 and ITER.LT.0, see description below), then the
* array A contains the factors L and U from the factorization
* A = P*L*U; the unit diagonal elements of L are not stored.
*
* LDA (input) INTEGER
* The leading dimension of the array A. LDA >= max(1,N).
*
* IPIV (output) INTEGER array, dimension (N)
* The pivot indices that define the permutation matrix P;
* row i of the matrix was interchanged with row IPIV(i).
* Corresponds either to the single precision factorization
* (if INFO.EQ.0 and ITER.GE.0) or the double precision
* factorization (if INFO.EQ.0 and ITER.LT.0).
*
* B (input) DOUBLE PRECISION array, dimension (LDB,NRHS)
* The N-by-NRHS matrix of right hand side matrix B.
*
* LDB (input) INTEGER
* The leading dimension of the array B. LDB >= max(1,N).
*
* X (output) DOUBLE PRECISION array, dimension (LDX,NRHS)
* If INFO = 0, the N-by-NRHS solution matrix X.
*
* LDX (input) INTEGER
* The leading dimension of the array X. LDX >= max(1,N).
*
* WORK (workspace) DOUBLE PRECISION array, dimension (N*NRHS)
* This array is used to hold the residual vectors.
*
* SWORK (workspace) REAL array, dimension (N*(N+NRHS))
* This array is used to use the single precision matrix and the
* right-hand sides or solutions in single precision.
*
* ITER (output) INTEGER
* < 0: iterative refinement has failed, double precision
* factorization has been performed
* -1 : taking into account machine parameters, N, NRHS, it
* is a priori not worth working in SINGLE PRECISION
* -2 : overflow of an entry when moving from double to
* SINGLE PRECISION
* -3 : failure of SGETRF
* -31: stop the iterative refinement after the 30th
* iterations
* > 0: iterative refinement has been sucessfully used.
* Returns the number of iterations
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: if INFO = i, U(i,i) computed in DOUBLE PRECISION is
* exactly zero. The factorization has been completed,
* but the factor U is exactly singular, so the solution
* could not be computed.
*
* =========
*
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