sposvx - use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A*X = B, where A is an N-by-N symmetric positive definite matrix and X and B are N-by-NRHS matrices
SUBROUTINE SPOSVX(FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO) CHARACTER*1 FACT, UPLO, EQUED INTEGER N, NRHS, LDA, LDAF, LDB, LDX, INFO INTEGER WORK2(*) REAL RCOND REAL A(LDA,*), AF(LDAF,*), S(*), B(LDB,*), X(LDX,*), FERR(*), BERR(*), WORK(*) SUBROUTINE SPOSVX_64(FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO) CHARACTER*1 FACT, UPLO, EQUED INTEGER*8 N, NRHS, LDA, LDAF, LDB, LDX, INFO INTEGER*8 WORK2(*) REAL RCOND REAL A(LDA,*), AF(LDAF,*), S(*), B(LDB,*), X(LDX,*), FERR(*), BERR(*), WORK(*) F95 INTERFACE SUBROUTINE POSVX(FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO) CHARACTER(LEN=1) :: FACT, UPLO, EQUED INTEGER :: N, NRHS, LDA, LDAF, LDB, LDX, INFO INTEGER, DIMENSION(:) :: WORK2 REAL :: RCOND REAL, DIMENSION(:) :: S, FERR, BERR, WORK REAL, DIMENSION(:,:) :: A, AF, B, X SUBROUTINE POSVX_64(FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO) CHARACTER(LEN=1) :: FACT, UPLO, EQUED INTEGER(8) :: N, NRHS, LDA, LDAF, LDB, LDX, INFO INTEGER(8), DIMENSION(:) :: WORK2 REAL :: RCOND REAL, DIMENSION(:) :: S, FERR, BERR, WORK REAL, DIMENSION(:,:) :: A, AF, B, X C INTERFACE #include <sunperf.h> void sposvx(char fact, char uplo, int n, int nrhs, float *a, int lda, float *af, int ldaf, char *equed, float *s, float *b, int ldb, float *x, int ldx, float *rcond, float *ferr, float *berr, int *info); void sposvx_64(char fact, char uplo, long n, long nrhs, float *a, long lda, float *af, long ldaf, char *equed, float *s, float *b, long ldb, float *x, long ldx, float *rcond, float *ferr, float *berr, long *info);
Oracle Solaris Studio Performance Library sposvx(3P)
NAME
sposvx - use the Cholesky factorization A = U**T*U or A = L*L**T to
compute the solution to a real system of linear equations A*X = B,
where A is an N-by-N symmetric positive definite matrix and X and B are
N-by-NRHS matrices
SYNOPSIS
SUBROUTINE SPOSVX(FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, EQUED,
S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO)
CHARACTER*1 FACT, UPLO, EQUED
INTEGER N, NRHS, LDA, LDAF, LDB, LDX, INFO
INTEGER WORK2(*)
REAL RCOND
REAL A(LDA,*), AF(LDAF,*), S(*), B(LDB,*), X(LDX,*), FERR(*), BERR(*),
WORK(*)
SUBROUTINE SPOSVX_64(FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, EQUED,
S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, WORK2, INFO)
CHARACTER*1 FACT, UPLO, EQUED
INTEGER*8 N, NRHS, LDA, LDAF, LDB, LDX, INFO
INTEGER*8 WORK2(*)
REAL RCOND
REAL A(LDA,*), AF(LDAF,*), S(*), B(LDB,*), X(LDX,*), FERR(*), BERR(*),
WORK(*)
F95 INTERFACE
SUBROUTINE POSVX(FACT, UPLO, N, NRHS, A, LDA, AF, LDAF,
EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK,
WORK2, INFO)
CHARACTER(LEN=1) :: FACT, UPLO, EQUED
INTEGER :: N, NRHS, LDA, LDAF, LDB, LDX, INFO
INTEGER, DIMENSION(:) :: WORK2
REAL :: RCOND
REAL, DIMENSION(:) :: S, FERR, BERR, WORK
REAL, DIMENSION(:,:) :: A, AF, B, X
SUBROUTINE POSVX_64(FACT, UPLO, N, NRHS, A, LDA, AF, LDAF,
EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK,
WORK2, INFO)
CHARACTER(LEN=1) :: FACT, UPLO, EQUED
INTEGER(8) :: N, NRHS, LDA, LDAF, LDB, LDX, INFO
INTEGER(8), DIMENSION(:) :: WORK2
REAL :: RCOND
REAL, DIMENSION(:) :: S, FERR, BERR, WORK
REAL, DIMENSION(:,:) :: A, AF, B, X
C INTERFACE
#include <sunperf.h>
void sposvx(char fact, char uplo, int n, int nrhs, float *a, int lda,
float *af, int ldaf, char *equed, float *s, float *b, int
ldb, float *x, int ldx, float *rcond, float *ferr, float
*berr, int *info);
void sposvx_64(char fact, char uplo, long n, long nrhs, float *a, long
lda, float *af, long ldaf, char *equed, float *s, float *b,
long ldb, float *x, long ldx, float *rcond, float *ferr,
float *berr, long *info);
PURPOSE
sposvx uses the Cholesky factorization A = U**T*U or A = L*L**T to com-
pute the solution to a real system of linear equations
A * X = B, where A is an N-by-N symmetric positive definite 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:
diag(S) * A * diag(S) * inv(diag(S)) * X = diag(S) * 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(S)*A*diag(S) and B by diag(S)*B.
2. If FACT = 'N' or 'E', the Cholesky decomposition is used to
factor the matrix A (after equilibration if FACT = 'E') as
A = U**T* U, if UPLO = 'U', or
A = L * L**T, if UPLO = 'L',
where U is an upper triangular matrix and L is a lower triangular
matrix.
3. If the leading i-by-i principal minor is not positive definite,
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(S) 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
contains the factored form of A. If EQUED = 'Y', the matrix
A has been equilibrated with scaling factors given by S. A
and AF will not be 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.
UPLO (input)
= 'U': Upper triangle of A is stored;
= 'L': Lower triangle of A is stored.
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 symmetric matrix A, except if FACT = 'F' and
EQUED = 'Y', then A must contain the equilibrated matrix
diag(S)*A*diag(S). If UPLO = 'U', the leading N-by-N upper
triangular part of A contains the upper triangular part of
the matrix A, and the strictly lower triangular part of A is
not referenced. If UPLO = 'L', the leading N-by-N lower tri-
angular part of A contains the lower triangular part of the
matrix A, and the strictly upper triangular part of A is not
referenced. A is not modified if FACT = 'F' or 'N', or if
FACT = 'E' and EQUED = 'N' on exit.
On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by
diag(S)*A*diag(S).
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 triangular factor U or L from the Cholesky factor-
ization A = U**T*U or A = L*L**T, in the same storage format
as A. If EQUED .ne. 'N', then AF is the factored form of the
equilibrated matrix diag(S)*A*diag(S).
If FACT = 'N', then AF is an output argument and on exit
returns the triangular factor U or L from the Cholesky fac-
torization A = U**T*U or A = L*L**T of the original matrix A.
If FACT = 'E', then AF is an output argument and on exit
returns the triangular factor U or L from the Cholesky fac-
torization A = U**T*U or A = L*L**T of the equilibrated
matrix A (see the description of A for the form of the equi-
librated matrix).
LDAF (input)
The leading dimension of the array AF. LDAF >= max(1,N).
EQUED (input or output)
Specifies the form of equilibration that was done. = 'N':
No equilibration (always true if FACT = 'N').
= 'Y': Equilibration was done, i.e., A has been replaced by
diag(S) * A * diag(S). EQUED is an input argument if FACT =
'F'; otherwise, it is an output argument.
S (input or output)
The scale factors for A; not accessed if EQUED = 'N'. S is
an input argument if FACT = 'F'; otherwise, S is an output
argument. If FACT = 'F' and EQUED = 'Y', each element of S
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 EQUED = 'Y', B is over-
written by diag(S) * 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 if EQUED = 'Y',
A and B are modified on exit, and the solution to the equili-
brated system is inv(diag(S))*X.
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)
dimension(3*N)
WORK2 (workspace)
dimension(N)
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: the leading minor of order i of A is not positive def-
inite, so the factorization could not be completed, and the
solution has not been computed. RCOND = 0 is returned. =
N+1: U is nonsingular, but RCOND is less than machine preci-
sion, meaning that the matrix is singular to working preci-
sion. Nevertheless, the solution and error bounds are com-
puted because there are a number of situations where the com-
puted solution can be more accurate than the value of RCOND
would suggest.
7 Nov 2015 sposvx(3P)