NAG Library Routine Document

f07nvf  (zsyrfs)

 Contents

    1  Purpose
    7  Accuracy

1
Purpose

f07nvf (zsyrfs) returns error bounds for the solution of a complex symmetric system of linear equations with multiple right-hand sides, AX=B. It improves the solution by iterative refinement, in order to reduce the backward error as much as possible.

2
Specification

Fortran Interface
Subroutine f07nvf ( uplo, n, nrhs, a, lda, af, ldaf, ipiv, b, ldb, x, ldx, ferr, berr, work, rwork, info)
Integer, Intent (In):: n, nrhs, lda, ldaf, ipiv(*), ldb, ldx
Integer, Intent (Out):: info
Real (Kind=nag_wp), Intent (Out):: ferr(nrhs), berr(nrhs), rwork(n)
Complex (Kind=nag_wp), Intent (In):: a(lda,*), af(ldaf,*), b(ldb,*)
Complex (Kind=nag_wp), Intent (Inout):: x(ldx,*)
Complex (Kind=nag_wp), Intent (Out):: work(2*n)
Character (1), Intent (In):: uplo
C Header Interface
#include nagmk26.h
void  f07nvf_ ( const char *uplo, const Integer *n, const Integer *nrhs, const Complex a[], const Integer *lda, const Complex af[], const Integer *ldaf, const Integer ipiv[], const Complex b[], const Integer *ldb, Complex x[], const Integer *ldx, double ferr[], double berr[], Complex work[], double rwork[], Integer *info, const Charlen length_uplo)
The routine may be called by its LAPACK name zsyrfs.

3
Description

f07nvf (zsyrfs) returns the backward errors and estimated bounds on the forward errors for the solution of a complex symmetric system of linear equations with multiple right-hand sides AX=B. The routine handles each right-hand side vector (stored as a column of the matrix B) independently, so we describe the function of f07nvf (zsyrfs) 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 – IntegerInput
On entry: n, the order of the matrix A.
Constraint: n0.
3:     nrhs – IntegerInput
On entry: r, the number of right-hand sides.
Constraint: nrhs0.
4:     alda* – Complex (Kind=nag_wp) arrayInput
Note: the second dimension of the array a must be at least max1,n.
On entry: the n by n original symmetric matrix A as supplied to f07nrf (zsytrf).
5:     lda – IntegerInput
On entry: the first dimension of the array a as declared in the (sub)program from which f07nvf (zsyrfs) is called.
Constraint: ldamax1,n.
6:     afldaf* – Complex (Kind=nag_wp) arrayInput
Note: the second dimension of the array af must be at least max1,n.
On entry: details of the factorization of A, as returned by f07nrf (zsytrf).
7:     ldaf – IntegerInput
On entry: the first dimension of the array af as declared in the (sub)program from which f07nvf (zsyrfs) is called.
Constraint: ldafmax1,n.
8:     ipiv* – Integer arrayInput
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 f07nrf (zsytrf).
9:     bldb* – Complex (Kind=nag_wp) arrayInput
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.
10:   ldb – IntegerInput
On entry: the first dimension of the array b as declared in the (sub)program from which f07nvf (zsyrfs) is called.
Constraint: ldbmax1,n.
11:   xldx* – Complex (Kind=nag_wp) arrayInput/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 f07nsf (zsytrs).
On exit: the improved solution matrix X.
12:   ldx – IntegerInput
On entry: the first dimension of the array x as declared in the (sub)program from which f07nvf (zsyrfs) is called.
Constraint: ldxmax1,n.
13:   ferrnrhs – Real (Kind=nag_wp) arrayOutput
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.
14:   berrnrhs – Real (Kind=nag_wp) arrayOutput
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.
15:   work2×n – Complex (Kind=nag_wp) arrayWorkspace
16:   rworkn – Real (Kind=nag_wp) arrayWorkspace
17:   info – IntegerOutput
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

f07nvf (zsyrfs) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f07nvf (zsyrfs) 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 16n2 real floating-point operations. Each step of iterative refinement involves an additional 24n2 real 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 linear equations of the form Ax=b; the number is usually 5 and never more than 11. Each solution involves approximately 8n2 real operations.
The real analogue of this routine is f07mhf (dsyrfs).

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= -0.39-0.71i 5.14-0.64i -7.86-2.96i 3.80+0.92i 5.14-0.64i 8.86+1.81i -3.52+0.58i 5.32-1.59i -7.86-2.96i -3.52+0.58i -2.83-0.03i -1.54-2.86i 3.80+0.92i 5.32-1.59i -1.54-2.86i -0.56+0.12i  
and
B= -55.64+41.22i -19.09-35.97i -48.18+66.00i -12.08-27.02i -0.49-01.47i 6.95+20.49i -6.43+19.24i -4.59-35.53i .  
Here A is symmetric and must first be factorized by f07nrf (zsytrf).

10.1
Program Text

Program Text (f07nvfe.f90)

10.2
Program Data

Program Data (f07nvfe.d)

10.3
Program Results

Program Results (f07nvfe.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017