Integer, Intent (In)	::	n, icolzp(), irowix(), iprm(7n), il(), iu(*), nrhs, ldb, ldx
Integer, Intent (Inout)	::	ifail
Real (Kind=nag_wp), Intent (In)	::	a(), lval(), uval(), b(ldb,)
Real (Kind=nag_wp), Intent (Inout)	::	x(ldx,*)
Real (Kind=nag_wp), Intent (Out)	::	ferr(nrhs), berr(nrhs)
Character (1), Intent (In)	::	trans

C Header Interface

#include <nag.h>

void

f11mhf_ (const char *trans, const Integer *n, const Integer icolzp[], const Integer irowix[], const double a[], const Integer iprm[], const Integer il[], const double lval[], const Integer iu[], const double uval[], const Integer *nrhs, const double b[], const Integer *ldb, double x[], const Integer *ldx, double ferr[], double berr[], Integer *ifail, const Charlen length_trans)

The routine may be called by the names f11mhf or nagf_sparse_direct_real_gen_refine.

3 Description

f11mhf returns the backward errors and estimated bounds on the forward errors for the solution of a real system of linear equations with multiple right-hand sides

A X = B

A^{T} X = B

. The routine handles each right-hand side vector (stored as a column of the matrix

B

) independently, so we describe the function of f11mhf in terms of a single right-hand side

b

and solution

x

Given a computed solution

x

, the routine computes the component-wise backward error

β

. This is the size of the smallest relative perturbation in each element of

A

and

b

such that if

x

is the exact solution of a perturbed system:

\begin{matrix} (A + δ A) x = b + δ b \\ then | δ a_{i j} | \leq β | a_{i j} | and | δ b_{i} | \leq β | b_{i} | . \end{matrix}

Then the routine estimates a bound for the component-wise forward error in the computed solution, defined by:

\max_{i}^{} | x_{i} - {\hat{x}}_{i} | / \max_{i}^{} | x_{i} |

where

\hat{x}

is the true solution.

The routine uses the

L U

factorization

P_{r} A P_{c} = L U

computed by f11mef and the solution computed by f11mff.

4 References

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

5 Arguments

1: $trans$ – Character(1) Input

On entry: specifies whether

A X = B

A^{T} X = B

is solved.

$trans ='N'$: $A X = B$ is solved.
$trans ='T'$: $A^{T} X = B$ is solved.

Constraint:

trans ='N'

'T'

2: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

3: $icolzp (*)$ – Integer array Input

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

n + 1

On entry: the new column index array of sparse matrix

A

. See Section 2.1.3 in the F11 Chapter Introduction.

4: $irowix (*)$ – Integer array Input

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

icolzp (n + 1) - 1

, the number of nonzeros of the sparse matrix

A

On entry: the row index array of sparse matrix

A

. See Section 2.1.3 in the F11 Chapter Introduction.

5: $a (*)$ – Real (Kind=nag_wp) array Input

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

icolzp (n + 1) - 1

, the number of nonzeros of the sparse matrix

A

On entry: the array of nonzero values in the sparse matrix

A

6: $iprm (7 \times n)$ – Integer array Input

On entry: the column permutation which defines

P_{c}

, the row permutation which defines

P_{r}

, plus associated data structures as computed by f11mef.

7: $il (*)$ – Integer array Input

Note: the dimension of the array il must be at least as large as the dimension of the array of the same name in f11mef.

On entry: records the sparsity pattern of matrix

L

as computed by f11mef.

8: $lval (*)$ – Real (Kind=nag_wp) array Input

Note: the dimension of the array lval must be at least as large as the dimension of the array of the same name in f11mef.

On entry: records the nonzero values of matrix

L

and some nonzero values of matrix

U

as computed by f11mef.

9: $iu (*)$ – Integer array Input

Note: the dimension of the array iu must be at least as large as the dimension of the array of the same name in f11mef.

On entry: records the sparsity pattern of matrix

U

as computed by f11mef.

10: $uval (*)$ – Real (Kind=nag_wp) array Input

Note: the dimension of the array uval must be at least as large as the dimension of the array of the same name in f11mef.

On entry: records some nonzero values of matrix

U

as computed by f11mef.

11: $nrhs$ – Integer Input

On entry:

nrhs

, the number of right-hand sides in

B

Constraint:

nrhs \geq 0

12: $b (ldb, *)$ – Real (Kind=nag_wp) array Input

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

\max (1, nrhs)

On entry: the

n \times nrhs

right-hand side matrix

B

13: $ldb$ – Integer Input

On entry: the first dimension of the array b as declared in the (sub)program from which f11mhf is called.

Constraint:

ldb \geq \max (1, n)

14: $x (ldx, *)$ – Real (Kind=nag_wp) array Input/Output

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

\max (1, nrhs)

On entry: the

n \times nrhs

solution matrix

X

, as returned by f11mff.

On exit: the

n \times nrhs

improved solution matrix

X

15: $ldx$ – Integer Input

On entry: the first dimension of the array x as declared in the (sub)program from which f11mhf is called.

Constraint:

ldx \geq \max (1, n)

16: $ferr (nrhs)$ – Real (Kind=nag_wp) array Output

On exit:

ferr (j)

contains an estimated error bound for the

j

th solution vector, that is, the

j

th column of

X

, for

j = 1, 2, \dots, nrhs

17: $berr (nrhs)$ – Real (Kind=nag_wp) array Output

On exit:

berr (j)

contains the component-wise backward error bound

β

for the

j

th solution vector, that is, the

j

th column of

X

, for

j = 1, 2, \dots, nrhs

18: $ifail$ – Integer Input/Output

On entry: ifail must be set to

0

−1

1

to set behaviour on detection of an error; these values have no effect when no error is detected.

A value of

0

causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of

−1

means that an error message is printed while a value of

1

means that it is not.

If halting is not appropriate, the value

−1

1

is recommended. If message printing is undesirable, then the value

1

is recommended. Otherwise, the value

0

is recommended. When the value $- 1$ or $1$ is used it is essential to test the value of ifail on exit.

On exit:

ifail = 0

unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

If on entry

ifail = 0

−1

, explanatory error messages are output on the current error message unit (as defined by x04aaf).

Errors or warnings detected by the routine:

$ifail = 1$: On entry, $ldb = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $ldb \geq \max (1, n)$ .

On entry, $ldx = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $ldx \geq \max (1, n)$ .

On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 0$ .

On entry, $nrhs = ⟨ value ⟩$ .
Constraint: $nrhs \geq 0$ .

On entry, $trans = ⟨ value ⟩$ .
Constraint: $trans ='N'$ or $'T'$ .

$ifail = 2$: Incorrect row permutations in array iprm.

$ifail = 3$: Incorrect column permutations in array iprm.

$ifail = - 99$: An unexpected error has been triggered by this routine. Please contact NAG.
See Section 7 in the Introduction to the NAG Library FL Interface for further information.

$ifail = - 399$: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library FL Interface for further information.

$ifail = - 999$: Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

The bounds returned in ferr are not rigorous, because they are estimated, not computed exactly; but in practice they almost always overestimate the actual error.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

f11mhf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

f11mhf makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.

Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

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 linear equations of the form

A x = b

A^{T} x = b

;

10 Example

This example solves the system of equations

A X = B

using iterative refinement and to compute the forward and backward error bounds, where

A = (\begin{matrix} 2.00 & 1.00 & 0 & 0 & 0 \\ 0 & 0 & 1.00 & - 1.00 & 0 \\ 4.00 & 0 & 1.00 & 0 & 1.00 \\ 0 & 0 & 0 & 1.00 & 2.00 \\ 0 & - 2.00 & 0 & 0 & 3.00 \end{matrix}) and B = (\begin{matrix} 1.56 & 3.12 \\ - 0.25 & - 0.50 \\ 3.60 & 7.20 \\ 1.33 & 2.66 \\ 0.52 & 1.04 \end{matrix}) .

Here

A

is nonsymmetric and must first be factorized by f11mef.

f11mh: FL CL CPP AD PY MB

NAG FL Interfacef11mhf (direct_​real_​gen_​refine)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG FL Interface
f11mhf (direct_real_gen_refine)