NAG FL Interface
f07phf (dsprfs)

1 Purpose

f07phf returns error bounds for the solution of a real symmetric indefinite system of linear equations with multiple right-hand sides, AX=B, using packed storage. It improves the solution by iterative refinement, in order to reduce the backward error as much as possible.

2 Specification

Fortran Interface
Subroutine f07phf ( uplo, n, nrhs, ap, afp, ipiv, b, ldb, x, ldx, ferr, berr, work, iwork, info)
Integer, Intent (In) :: n, nrhs, ipiv(*), ldb, ldx
Integer, Intent (Out) :: iwork(n), info
Real (Kind=nag_wp), Intent (In) :: ap(*), afp(*), b(ldb,*)
Real (Kind=nag_wp), Intent (Inout) :: x(ldx,*)
Real (Kind=nag_wp), Intent (Out) :: ferr(nrhs), berr(nrhs), work(3*n)
Character (1), Intent (In) :: uplo
C Header Interface
#include <nag.h>
void  f07phf_ (const char *uplo, const Integer *n, const Integer *nrhs, const double ap[], const double afp[], const Integer ipiv[], const double b[], const Integer *ldb, double x[], const Integer *ldx, double ferr[], double berr[], double work[], Integer iwork[], Integer *info, const Charlen length_uplo)
The routine may be called by the names f07phf, nagf_lapacklin_dsprfs or its LAPACK name dsprfs.

3 Description

f07phf returns the backward errors and estimated bounds on the forward errors for the solution of a real symmetric indefinite system of linear equations with multiple right-hand sides AX=B, using packed storage. The routine handles each right-hand side vector (stored as a column of the matrix B) independently, so we describe the function of f07phf 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 x is the exact solution of a perturbed system
A+δAx=b+δb δaijβaij   and   δbiβbi .  
Then the routine estimates a bound for the component-wise forward error in the computed solution, defined by:
maxixi-x^i/maxixi  
where x^ is the true solution.
For details of the method, see the F07 Chapter Introduction.

4 References

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

5 Arguments

1: uplo Character(1) Input
On entry: specifies whether the upper or lower triangular part of A is stored and how A is to be factorized.
uplo='U'
The upper triangular part of A is stored and A is factorized as PUDUTPT, where U is upper triangular.
uplo='L'
The lower triangular part of A is stored and A is factorized as PLDLTPT, where L is lower triangular.
Constraint: uplo='U' or 'L'.
2: n Integer Input
On entry: n, the order of the matrix A.
Constraint: n0.
3: nrhs Integer Input
On entry: r, the number of right-hand sides.
Constraint: nrhs0.
4: ap* Real (Kind=nag_wp) array Input
Note: the dimension of the array ap must be at least max1,n×n+1/2.
On entry: the n by n original symmetric matrix A as supplied to f07pdf.
5: afp* Real (Kind=nag_wp) array Input
Note: the dimension of the array afp must be at least max1,n×n+1/2.
On entry: the factorization of A stored in packed form, as returned by f07pdf.
6: ipiv* Integer array Input
Note: the dimension of the array ipiv must be at least max1,n.
On entry: details of the interchanges and the block structure of D, as returned by f07pdf.
7: bldb* Real (Kind=nag_wp) array Input
Note: the second dimension of the array b must be at least max1,nrhs.
On entry: the n by r right-hand side matrix B.
8: ldb Integer Input
On entry: the first dimension of the array b as declared in the (sub)program from which f07phf is called.
Constraint: ldbmax1,n.
9: xldx* Real (Kind=nag_wp) array Input/Output
Note: the second dimension of the array x must be at least max1,nrhs.
On entry: the n by r solution matrix X, as returned by f07pef.
On exit: the improved solution matrix X.
10: ldx Integer Input
On entry: the first dimension of the array x as declared in the (sub)program from which f07phf is called.
Constraint: ldxmax1,n.
11: ferrnrhs Real (Kind=nag_wp) array Output
On exit: ferrj contains an estimated error bound for the jth solution vector, that is, the jth column of X, for j=1,2,,r.
12: berrnrhs Real (Kind=nag_wp) array Output
On exit: berrj contains the component-wise backward error bound β for the jth solution vector, that is, the jth column of X, for j=1,2,,r.
13: work3×n Real (Kind=nag_wp) array Workspace
14: iworkn Integer array Workspace
15: info Integer Output
On exit: info=0 unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

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

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

f07phf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f07phf 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

For each right-hand side, computation of the backward error involves a minimum of 4n2 floating-point operations. Each step of iterative refinement involves an additional 6n2 operations. At most five steps of iterative refinement are performed, but usually only 1 or 2 steps are required.
Estimating the forward error involves solving a number of systems of linear equations of the form Ax=b; the number is usually 4 or 5 and never more than 11. Each solution involves approximately 2n2 operations.
The complex analogues of this routine are f07pvf for Hermitian matrices and f07qvf for symmetric matrices.

10 Example

This example solves the system of equations AX=B using iterative refinement and to compute the forward and backward error bounds, where
A= 2.07 3.87 4.20 -1.15 3.87 -0.21 1.87 0.63 4.20 1.87 1.15 2.06 -1.15 0.63 2.06 -1.81   and   B= -9.50 27.85 -8.38 9.90 -6.07 19.25 -0.96 3.93 .  
Here A is symmetric indefinite, stored in packed form, and must first be factorized by f07pdf.

10.1 Program Text

Program Text (f07phfe.f90)

10.2 Program Data

Program Data (f07phfe.d)

10.3 Program Results

Program Results (f07phfe.r)