NAG Library Routine Document

F07MBF (DSYSVX)

INTEGER	N, NRHS, LDA, LDAF, IPIV(), LDB, LDX, LWORK, IWORK(), INFO
REAL (KIND=nag_wp)	A(LDA,), AF(LDAF,), B(LDB,), X(LDX,), RCOND, FERR(), BERR(), WORK(max(1,LWORK))
CHARACTER(1)	FACT, UPLO

The routine may be called by its LAPACK name dsysvx.

3 Description

F07MBF (DSYSVX) performs the following steps:

If $FACT ='N'$ , the diagonal pivoting method is used to factor $A$ . The form of the factorization is $A = U D U^{T}$ if $UPLO ='U'$ or $A = L D L^{T}$ if $UPLO ='L'$ , where $U$ (or $L$ ) is a product of permutation and unit upper (lower) triangular matrices, and $D$ is symmetric and block diagonal with $1$ by $1$ and $2$ by $2$ diagonal blocks.
If some $d_{i i} = 0$ , so that $D$ 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.
The system of equations is solved for $X$ using the factored form of $A$ .
Iterative refinement is applied to improve the computed solution matrix and to calculate error bounds and backward error estimates for it.

4 References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia http://www.netlib.org/lapack/lug

Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

Higham N J (2002) Accuracy and Stability of Numerical Algorithms (2nd Edition) SIAM, Philadelphia

5 Parameters

1: FACT – CHARACTER(1)Input

On entry: specifies whether or not the factorized form of the matrix

A

has been supplied.

$FACT ='F'$: AF and IPIV contain the factorized form of the matrix $A$ . AF and IPIV will not be modified.
$FACT ='N'$: The matrix $A$ will be copied to AF and factorized.

Constraint:

FACT ='F'

'N'

2: UPLO – CHARACTER(1)Input

On entry: if

UPLO ='U'

, the upper triangle of

A

is stored.

UPLO ='L'

, the lower triangle of

A

is stored.

Constraint:

UPLO ='U'

'L'

3: N – INTEGERInput

On entry:

n

, the number of linear equations, i.e., the order of the matrix

A

Constraint:

N \geq 0

4: NRHS – INTEGERInput

On entry:

r

, the number of right-hand sides, i.e., the number of columns of the matrix

B

Constraint:

NRHS \geq 0

5: A(LDA, $*$ ) – REAL (KIND=nag_wp) arrayInput

Note: the second dimension of the array A must be at least

\max (1, N)

On entry: the

n

n

symmetric matrix

A

If $UPLO ='U'$ , the upper triangular part of $A$ must be stored and the elements of the array below the diagonal are not referenced.
If $UPLO ='L'$ , the lower triangular part of $A$ must be stored and the elements of the array above the diagonal are not referenced.

6: LDA – INTEGERInput

On entry: the first dimension of the array A as declared in the (sub)program from which F07MBF (DSYSVX) is called.

Constraint:

LDA \geq \max (1, N)

7: AF(LDAF, $*$ ) – REAL (KIND=nag_wp) arrayInput/Output

Note: the second dimension of the array AF must be at least

\max (1, N)

On entry: if

FACT ='F'

, AF contains the block diagonal matrix

D

and the multipliers used to obtain the factor

U

L

from the factorization

A = U D U^{T}

A = L D L^{T}

as computed by F07MDF (DSYTRF).

On exit: if

FACT ='N'

, AF returns the block diagonal matrix

D

and the multipliers used to obtain the factor

U

L

from the factorization

A = U D U^{T}

A = L D L^{T}

8: LDAF – INTEGERInput

On entry: the first dimension of the array AF as declared in the (sub)program from which F07MBF (DSYSVX) is called.

Constraint:

LDAF \geq \max (1, N)

9: IPIV( $*$ ) – INTEGER arrayInput/Output

Note: the dimension of the array IPIV must be at least

\max (1, N)

On entry: if

FACT ='F'

, IPIV contains details of the interchanges and the block structure of

D

, as determined by F07MDF (DSYTRF).

if $IPIV (i) = k > 0$ , $d_{i i}$ is a $1$ by $1$ pivot block and the $i$ th row and column of $A$ were interchanged with the $k$ th row and column;
if $UPLO ='U'$ and $IPIV (i - 1) = IPIV (i) = - l < 0$ , $(\begin{matrix} d_{i - 1, i - 1} & {\bar{d}}_{i, i - 1} \\ {\bar{d}}_{i, i - 1} & d_{i i} \end{matrix})$ is a $2$ by $2$ pivot block and the $(i - 1)$ th row and column of $A$ were interchanged with the $l$ th row and column;
if $UPLO ='L'$ and $IPIV (i) = IPIV (i + 1) = - m < 0$ , $(\begin{matrix} d_{i i} & d_{i + 1, i} \\ d_{i + 1, i} & d_{i + 1, i + 1} \end{matrix})$ is a $2$ by $2$ pivot block and the $(i + 1)$ th row and column of $A$ were interchanged with the $m$ th row and column.

On exit: if

FACT ='N'

, IPIV contains details of the interchanges and the block structure of

D

, as determined by F07MDF (DSYTRF), as described above.

10: B(LDB, $*$ ) – REAL (KIND=nag_wp) arrayInput

Note: the second dimension of the array B must be at least

\max (1, NRHS)

On entry: the

n

r

right-hand side matrix

B

11: LDB – INTEGERInput

On entry: the first dimension of the array B as declared in the (sub)program from which F07MBF (DSYSVX) is called.

Constraint:

LDB \geq \max (1, N)

12: X(LDX, $*$ ) – REAL (KIND=nag_wp) arrayOutput

Note: the second dimension of the array X must be at least

\max (1, NRHS)

On exit: if

INFO = 0

N + 1

, the

n

r

solution matrix

X

13: LDX – INTEGERInput

On entry: the first dimension of the array X as declared in the (sub)program from which F07MBF (DSYSVX) is called.

Constraint:

LDX \geq \max (1, N)

14: RCOND – REAL (KIND=nag_wp)Output

On exit: the estimate of the reciprocal condition number of the matrix

A

. If

RCOND = 0.0

, the matrix may be exactly singular. This condition is indicated by

INFO > 0 and INFO \leq N

. Otherwise, if RCOND is less than the machine precision, the matrix is singular to working precision. This condition is indicated by

INFO = N + 1

15: FERR( $*$ ) – REAL (KIND=nag_wp) arrayOutput

Note: the dimension of the array FERR must be at least

\max (1, NRHS)

On exit: if

INFO = 0

N + 1

, an estimate of the forward error bound for each computed solution vector, such that

{‖{\hat{x}}_{j} - x_{j}‖}_{\infty} / {‖x_{j}‖}_{\infty} \leq FERR (j)

where

{\hat{x}}_{j}

is the

j

th column of the computed solution returned in the array X and

x_{j}

is the corresponding column of the exact solution

X

. The estimate is as reliable as the estimate for RCOND, and is almost always a slight overestimate of the true error.

16: BERR( $*$ ) – REAL (KIND=nag_wp) arrayOutput

Note: the dimension of the array BERR must be at least

\max (1, NRHS)

On exit: if

INFO = 0

N + 1

, an estimate of the component-wise relative backward error of each computed solution vector

{\hat{x}}_{j}

(i.e., the smallest relative change in any element of

A

B

that makes

{\hat{x}}_{j}

an exact solution).

17: WORK( $\max (1, LWORK)$ ) – REAL (KIND=nag_wp) arrayWorkspace

On exit: if

INFO = 0

WORK (1)

returns the optimal LWORK.

18: LWORK – INTEGERInput

On entry: the dimension of the array WORK as declared in the (sub)program from which F07MBF (DSYSVX) is called.

LWORK \geq \max (1, 3 \times N)

, and for best performance, when

FACT ='N'

LWORK \geq \max (1, 3 \times N, N \times nb)

, where

nb

is the optimal block size for F07MDF (DSYTRF).

LWORK = - 1

, a workspace query is assumed; the routine only calculates the optimal size of the WORK array, returns this value as the first entry of the WORK array, and no error message related to LWORK is issued.

19: IWORK( $*$ ) – INTEGER arrayWorkspace

Note: the dimension of the array IWORK must be at least

\max (1, N)

20: INFO – INTEGEROutput

On exit:

INFO = 0

unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

Errors or warnings detected by the routine:

$INFO < 0$: If $INFO = - i$ , the $i$ th argument had an illegal value. An explanatory message is output, and execution of the program is terminated.

$INFO > 0 and INFO \leq N$: If $INFO \leq N$ , $d (i, i)$ is exactly zero. The factorization has been completed, but the factor $D$ is exactly singular, so the solution and error bounds could not be computed. $RCOND = 0.0$ is returned.

$INFO = N + 1$: $D$ 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 Accuracy

For each right-hand side vector

b

, the computed solution

\hat{x}

is the exact solution of a perturbed system of equations

(A + E) \hat{x} = b

, where

{‖E‖}_{1} = O (ε) {‖A‖}_{1},

where

ε

is the machine precision. See Chapter 11 of Higham (2002) for further details.

\hat{x}

is the true solution, then the computed solution

x

satisfies a forward error bound of the form

\frac{{‖x - \hat{x}‖}_{\infty}}{{‖\hat{x}‖}_{\infty}} \leq w_{c} cond (A, \hat{x}, b)

where

cond (A, \hat{x}, b) = {‖|A^{- 1}| (|A| |\hat{x}| + |b|)‖}_{\infty} / {‖\hat{x}‖}_{\infty} \leq cond (A) = {‖|A^{- 1}| |A|‖}_{\infty} \leq κ_{\infty} (A)

. If

\hat{x}

is the

j

th column of

X

, then

w_{c}

is returned in

BERR (j)

and a bound on

{‖x - \hat{x}‖}_{\infty} / {‖\hat{x}‖}_{\infty}

is returned in

FERR (j)

. See Section 4.4 of Anderson et al. (1999) for further details.

8 Further Comments

The factorization of

A

requires approximately

\frac{1}{3} n^{3}

floating point operations.

For each right-hand side, computation of the backward error involves a minimum of

4 n^{2}

floating point operations. Each step of iterative refinement involves an additional

6 n^{2}

operations. At most five steps of iterative refinement are performed, but usually only one or two steps are required. Estimating the forward error involves solving a number of systems of equations of the form

A x = b

; the number is usually

4

5

and never more than

11

. Each solution involves approximately

2 n^{2}

operations.

The complex analogues of this routine are F07MPF (ZHESVX) for Hermitian matrices, and F07NPF (ZSYSVX) for symmetric matrices.

9 Example

This example solves the equations

A X = B,

where

A

is the symmetric matrix

A = (\begin{matrix} - 1.81 & 2.06 & 0.63 & - 1.15 \\ 2.06 & 1.15 & 1.87 & 4.20 \\ 0.63 & 1.87 & - 0.21 & 3.87 \\ - 1.15 & 4.20 & 3.87 & 2.07 \end{matrix}) and B = (\begin{matrix} 0.96 & 3.93 \\ 6.07 & 19.25 \\ 8.38 & 9.90 \\ 9.50 & 27.85 \end{matrix}) .

Error estimates for the solutions, and an estimate of the reciprocal of the condition number of the matrix

A

are also output.

NAG Library Routine DocumentF07MBF (DSYSVX)

+− Contents

1 Purpose

2 Specification

3 Description

4 References

5 Parameters

6 Error Indicators and Warnings

7 Accuracy

8 Further Comments

9 Example

9.1 Program Text

9.2 Program Data

9.3 Program Results

NAG Library Routine Document

F07MBF (DSYSVX)