cgesvx - use the LU factorization to compute the solution to a complex system of linear equations A*X=B, where is an N-by-N general matrix
SUBROUTINE CGESVX(FACT, TRANSA, N, NRHS, A, LDA, AF, LDAF, IPIVOT, EQUED, R, C, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO) CHARACTER*1 FACT, TRANSA, EQUED COMPLEX A(LDA,*), AF(LDAF,*), B(LDB,*), X(LDX,*), WORK(*) INTEGER N, NRHS, LDA, LDAF, LDB, LDX, INFO INTEGER IPIVOT(*) REAL RCOND REAL R(*), C(*), FERR(*), BERR(*), WORK2(*) SUBROUTINE CGESVX_64(FACT, TRANSA, N, NRHS, A, LDA, AF, LDAF, IPIVOT, EQUED, R, C, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO) CHARACTER*1 FACT, TRANSA, EQUED COMPLEX A(LDA,*), AF(LDAF,*), B(LDB,*), X(LDX,*), WORK(*) INTEGER*8 N, NRHS, LDA, LDAF, LDB, LDX, INFO INTEGER*8 IPIVOT(*) REAL RCOND REAL R(*), C(*), FERR(*), BERR(*), WORK2(*) F95 INTERFACE SUBROUTINE GESVX(FACT, TRANSA, N, NRHS, A, LDA, AF, LDAF, IPIVOT, EQUED, R, C, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO) CHARACTER(LEN=1) :: FACT, TRANSA, EQUED COMPLEX, DIMENSION(:) :: WORK COMPLEX, DIMENSION(:,:) :: A, AF, B, X INTEGER :: N, NRHS, LDA, LDAF, LDB, LDX, INFO INTEGER, DIMENSION(:) :: IPIVOT REAL :: RCOND REAL, DIMENSION(:) :: R, C, FERR, BERR, WORK2 SUBROUTINE GESVX_64(FACT, TRANSA, N, NRHS, A, LDA, AF, LDAF, IPIVOT, EQUED, R, C, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO) CHARACTER(LEN=1) :: FACT, TRANSA, EQUED COMPLEX, DIMENSION(:) :: WORK COMPLEX, DIMENSION(:,:) :: A, AF, B, X INTEGER(8) :: N, NRHS, LDA, LDAF, LDB, LDX, INFO INTEGER(8), DIMENSION(:) :: IPIVOT REAL :: RCOND REAL, DIMENSION(:) :: R, C, FERR, BERR, WORK2 C INTERFACE #include <sunperf.h> void cgesvx(char fact, char transa, int n, int nrhs, complex *a, int lda, complex *af, int ldaf, int *ipivot, char *equed, float *r, float *c, complex *b, int ldb, complex *x, int ldx, float *rcond, float *ferr, float *berr, float *work2, int *info); void cgesvx_64(char fact, char transa, long n, long nrhs, complex *a, long lda, complex *af, long ldaf, long *ipivot, char *equed, float *r, float *c, complex *b, long ldb, complex *x, long ldx, float *rcond, float *ferr, float *berr, float *work2, long *info);
Oracle Solaris Studio Performance Library cgesvx(3P)
NAME
cgesvx - use the LU factorization to compute the solution to a complex
system of linear equations A*X=B, where is an N-by-N general matrix
SYNOPSIS
SUBROUTINE CGESVX(FACT, TRANSA, N, NRHS, A, LDA, AF, LDAF, IPIVOT,
EQUED, R, C, B, LDB, X, LDX, RCOND, FERR, BERR, WORK,
WORK2, INFO)
CHARACTER*1 FACT, TRANSA, EQUED
COMPLEX A(LDA,*), AF(LDAF,*), B(LDB,*), X(LDX,*), WORK(*)
INTEGER N, NRHS, LDA, LDAF, LDB, LDX, INFO
INTEGER IPIVOT(*)
REAL RCOND
REAL R(*), C(*), FERR(*), BERR(*), WORK2(*)
SUBROUTINE CGESVX_64(FACT, TRANSA, N, NRHS, A, LDA, AF, LDAF, IPIVOT,
EQUED, R, C, B, LDB, X, LDX, RCOND, FERR, BERR, WORK,
WORK2, INFO)
CHARACTER*1 FACT, TRANSA, EQUED
COMPLEX A(LDA,*), AF(LDAF,*), B(LDB,*), X(LDX,*), WORK(*)
INTEGER*8 N, NRHS, LDA, LDAF, LDB, LDX, INFO
INTEGER*8 IPIVOT(*)
REAL RCOND
REAL R(*), C(*), FERR(*), BERR(*), WORK2(*)
F95 INTERFACE
SUBROUTINE GESVX(FACT, TRANSA, N, NRHS, A, LDA, AF, LDAF,
IPIVOT, EQUED, R, C, B, LDB, X, LDX, RCOND, FERR,
BERR, WORK, WORK2, INFO)
CHARACTER(LEN=1) :: FACT, TRANSA, EQUED
COMPLEX, DIMENSION(:) :: WORK
COMPLEX, DIMENSION(:,:) :: A, AF, B, X
INTEGER :: N, NRHS, LDA, LDAF, LDB, LDX, INFO
INTEGER, DIMENSION(:) :: IPIVOT
REAL :: RCOND
REAL, DIMENSION(:) :: R, C, FERR, BERR, WORK2
SUBROUTINE GESVX_64(FACT, TRANSA, N, NRHS, A, LDA, AF, LDAF,
IPIVOT, EQUED, R, C, B, LDB, X, LDX, RCOND, FERR,
BERR, WORK, WORK2, INFO)
CHARACTER(LEN=1) :: FACT, TRANSA, EQUED
COMPLEX, DIMENSION(:) :: WORK
COMPLEX, DIMENSION(:,:) :: A, AF, B, X
INTEGER(8) :: N, NRHS, LDA, LDAF, LDB, LDX, INFO
INTEGER(8), DIMENSION(:) :: IPIVOT
REAL :: RCOND
REAL, DIMENSION(:) :: R, C, FERR, BERR, WORK2
C INTERFACE
#include <sunperf.h>
void cgesvx(char fact, char transa, int n, int nrhs, complex *a, int
lda, complex *af, int ldaf, int *ipivot, char *equed, float
*r, float *c, complex *b, int ldb, complex *x, int ldx, float
*rcond, float *ferr, float *berr, float *work2, int *info);
void cgesvx_64(char fact, char transa, long n, long nrhs, complex *a,
long lda, complex *af, long ldaf, long *ipivot, char *equed,
float *r, float *c, complex *b, long ldb, complex *x, long
ldx, float *rcond, float *ferr, float *berr, float *work2,
long *info);
PURPOSE
cgesvx uses the LU factorization to compute the solution to a complex
system of linear equations
A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS
matrices.
Error bounds on the solution and a condition estimate are also pro-
vided.
The following steps are performed:
1. If FACT = 'E', real scaling factors are computed to equilibrate
the system:
TRANS = 'N': diag(R)*A*diag(C) *inv(diag(C))*X = diag(R)*B
TRANS = 'T': (diag(R)*A*diag(C))**T *inv(diag(R))*X = diag(C)*B
TRANS = 'C': (diag(R)*A*diag(C))**H *inv(diag(R))*X = diag(C)*B
Whether or not the system will be equilibrated depends on the
scaling of the matrix A, but if equilibration is used, A is
overwritten by diag(R)*A*diag(C) and B by diag(R)*B (if TRANS='N')
or diag(C)*B (if TRANS = 'T' or 'C').
2. If FACT = 'N' or 'E', the LU decomposition is used to factor the
matrix A (after equilibration if FACT = 'E') as
A = P * L * U,
where P is a permutation matrix, L is a unit lower triangular
matrix, and U is upper triangular.
3. If some U(i,i)=0, so that U is exactly singular, then the routine
returns with INFO = i. Otherwise, the factored form of A is used
to estimate the condition number of the matrix A. If the
reciprocal of the condition number is less than machine precision,
INFO = N+1 is returned as a warning, but the routine still goes on
to solve for X and compute error bounds as described below.
4. The system of equations is solved for X using the factored form
of A.
5. Iterative refinement is applied to improve the computed solution
matrix and calculate error bounds and backward error estimates
for it.
6. If equilibration was used, the matrix X is premultiplied by
diag(C) (if TRANS = 'N') or diag(R) (if TRANS = 'T' or 'C') so
that it solves the original system before equilibration.
ARGUMENTS
FACT (input)
Specifies whether or not the factored form of the matrix A is
supplied on entry, and if not, whether the matrix A should be
equilibrated before it is factored. = 'F': On entry, AF and
IPIVOT contain the factored form of A. If EQUED is not 'N',
the matrix A has been equilibrated with scaling factors given
by R and C. A, AF, and IPIVOT are not modified. = 'N': The
matrix A will be copied to AF and factored.
= 'E': The matrix A will be equilibrated if necessary, then
copied to AF and factored.
TRANSA (input)
Specifies the form of the system of equations:
= 'N': A * X = B (No transpose)
= 'T': A**T * X = B (Transpose)
= 'C': A**H * X = B (Conjugate transpose)
N (input) The number of linear equations, i.e., the order of the matrix
A. N >= 0.
NRHS (input)
The number of right hand sides, i.e., the number of columns
of the matrices B and X. NRHS >= 0.
A (input/output)
On entry, the N-by-N matrix A. If FACT = 'F' and EQUED is
not 'N', then A must have been equilibrated by the scaling
factors in R and/or C. A is not modified if FACT = 'F' or
'N', or if FACT = 'E' and EQUED = 'N' on exit.
On exit, if EQUED .ne. 'N', A is scaled as follows: EQUED =
'R': A := diag(R) * A
EQUED = 'C': A := A * diag(C)
EQUED = 'B': A := diag(R) * A * diag(C).
LDA (input)
The leading dimension of the array A. LDA >= max(1,N).
AF (input or output)
If FACT = 'F', then AF is an input argument and on entry con-
tains the factors L and U from the factorization A = P*L*U as
computed by CGETRF. If EQUED .ne. 'N', then AF is the fac-
tored form of the equilibrated matrix A.
If FACT = 'N', then AF is an output argument and on exit
returns the factors L and U from the factorization A = P*L*U
of the original matrix A.
If FACT = 'E', then AF is an output argument and on exit
returns the factors L and U from the factorization A = P*L*U
of the equilibrated matrix A (see the description of A for
the form of the equilibrated matrix).
LDAF (input)
The leading dimension of the array AF. LDAF >= max(1,N).
IPIVOT (input or output)
If FACT = 'F', then IPIVOT is an input argument and on entry
contains the pivot indices from the factorization A = P*L*U
as computed by CGETRF; row i of the matrix was interchanged
with row IPIVOT(i).
If FACT = 'N', then IPIVOT is an output argument and on exit
contains the pivot indices from the factorization A = P*L*U
of the original matrix A.
If FACT = 'E', then IPIVOT is an output argument and on exit
contains the pivot indices from the factorization A = P*L*U
of the equilibrated matrix A.
EQUED (input or output)
Specifies the form of equilibration that was done. = 'N':
No equilibration (always true if FACT = 'N').
= 'R': Row equilibration, i.e., A has been premultiplied by
diag(R). = 'C': Column equilibration, i.e., A has been
postmultiplied by diag(C). = 'B': Both row and column equi-
libration, i.e., A has been replaced by diag(R) * A *
diag(C). EQUED is an input argument if FACT = 'F'; other-
wise, it is an output argument.
R (input or output)
The row scale factors for A. If EQUED = 'R' or 'B', A is
multiplied on the left by diag(R); if EQUED = 'N' or 'C', R
is not accessed. R is an input argument if FACT = 'F'; oth-
erwise, R is an output argument. If FACT = 'F' and EQUED =
'R' or 'B', each element of R must be positive.
C (input or output)
The column scale factors for A. If EQUED = 'C' or 'B', A is
multiplied on the right by diag(C); if EQUED = 'N' or 'R', C
is not accessed. C is an input argument if FACT = 'F'; oth-
erwise, C is an output argument. If FACT = 'F' and EQUED =
'C' or 'B', each element of C must be positive.
B (input/output)
On entry, the N-by-NRHS right hand side matrix B. On exit,
if EQUED = 'N', B is not modified; if TRANSA = 'N' and EQUED
= 'R' or 'B', B is overwritten by diag(R)*B; if TRANSA = 'T'
or 'C' and EQUED = 'C' or 'B', B is overwritten by diag(C)*B.
LDB (input)
The leading dimension of the array B. LDB >= max(1,N).
X (output)
If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to
the original system of equations. Note that A and B are mod-
ified on exit if EQUED .ne. 'N', and the solution to the
equilibrated system is inv(diag(C))*X if TRANSA = 'N' and
EQUED = 'C' or 'B', or inv(diag(R))*X if TRANSA = 'T' or 'C'
and EQUED = 'R' or 'B'.
LDX (input)
The leading dimension of the array X. LDX >= max(1,N).
RCOND (output)
The estimate of the reciprocal condition number of the matrix
A after equilibration (if done). If RCOND is less than the
machine precision (in particular, if RCOND = 0), the matrix
is singular to working precision. This condition is indi-
cated by a return code of INFO > 0.
FERR (output)
The estimated forward error bound for each solution vector
X(j) (the j-th column of the solution matrix X). If XTRUE is
the true solution corresponding to X(j), FERR(j) is an esti-
mated upper bound for the magnitude of the largest element in
(X(j) - XTRUE) divided by the magnitude of the largest ele-
ment in X(j). The estimate is as reliable as the estimate
for RCOND, and is almost always a slight overestimate of the
true error.
BERR (output)
The componentwise relative backward error of each solution
vector X(j) (i.e., the smallest relative change in any ele-
ment of A or B that makes X(j) an exact solution).
WORK (workspace)
WORK is COMPLEX array, dimension(2*N)
WORK2 (output)
WORK2 is REAL array, dimension(2*N) On exit, WORK2(1) con-
tains the reciprocal pivot growth factor norm(A)/norm(U). The
"max absolute element" norm is used. If WORK2(1) is much less
than 1, then the stability of the LU factorization of the
(equilibrated) matrix A could be poor. This also means that
the solution X, condition estimator RCOND, and forward error
bound FERR could be unreliable. If factorization fails with
0<INFO<=N, then WORK2(1) contains the reciprocal pivot growth
factor for the leading INFO columns of A.
INFO (output)
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, and i is
<= N: U(i,i) is exactly zero. The factorization has been
completed, but the factor U is exactly singular, so the solu-
tion and error bounds could not be computed. RCOND = 0 is
returned. = N+1: U is nonsingular, but RCOND is less than
machine precision, meaning that the matrix is singular to
working precision. Nevertheless, the solution and error
bounds are computed because there are a number of situations
where the computed solution can be more accurate than the
value of RCOND would suggest.
7 Nov 2015 cgesvx(3P)