NAG Library Routine Document
f11duf
(complex_gen_solve_bdilu)
1
Purpose
f11duf solves a complex sparse non-Hermitian system of linear equations, represented in coordinate storage format, using a restarted generalized minimal residual (RGMRES), conjugate gradient squared (CGS), stabilized bi-conjugate gradient (Bi-CGSTAB), or transpose-free quasi-minimal residual (TFQMR) method, with block Jacobi or additive Schwarz preconditioning.
2
Specification
Fortran Interface
Subroutine f11duf ( |
method,
n,
nnz,
a,
la,
irow,
icol,
nb,
istb,
indb,
lindb,
ipivp,
ipivq,
istr,
idiag,
b,
m,
tol,
maxitn,
x,
rnorm,
itn,
work,
lwork,
ifail) |
Integer, Intent (In) | :: |
n,
nnz,
la,
irow(la),
icol(la),
nb,
istb(nb+1),
indb(lindb),
lindb,
istr(lindb+1),
idiag(lindb),
m,
maxitn,
lwork | Integer, Intent (Inout) | :: |
ipivp(lindb),
ipivq(lindb),
ifail | Integer, Intent (Out) | :: |
itn | Real (Kind=nag_wp), Intent (In) | :: |
tol | Real (Kind=nag_wp), Intent (Out) | :: |
rnorm | Complex (Kind=nag_wp), Intent (In) | :: |
a(la),
b(n) | Complex (Kind=nag_wp), Intent (Inout) | :: |
x(n) | Complex (Kind=nag_wp), Intent (Out) | :: |
work(lwork) | Character (*), Intent (In) | :: |
method |
|
C Header Interface
#include nagmk26.h
void |
f11duf_ (
const char *method,
const Integer *n,
const Integer *nnz,
const Complex a[],
const Integer *la,
const Integer irow[],
const Integer icol[],
const Integer *nb,
const Integer istb[],
const Integer indb[],
const Integer *lindb,
Integer ipivp[],
Integer ipivq[],
const Integer istr[],
const Integer idiag[],
const Complex b[],
const Integer *m,
const double *tol,
const Integer *maxitn,
Complex x[],
double *rnorm,
Integer *itn,
Complex work[],
const Integer *lwork,
Integer *ifail,
const Charlen length_method) |
|
3
Description
f11duf solves a complex sparse non-Hermitian linear system of equations
using a preconditioned RGMRES (see
Saad and Schultz (1986)), CGS (see
Sonneveld (1989)), Bi-CGSTAB(
) (see
Van der Vorst (1989) and
Sleijpen and Fokkema (1993)), or TFQMR (see
Freund and Nachtigal (1991) and
Freund (1993)) method.
f11duf uses the incomplete (possibly overlapping) block
factorization determined by
f11dtf as the preconditioning matrix. A call to
f11duf must always be preceded by a call to
f11dtf. Alternative preconditioners for the same storage scheme are available by calling
f11dqf or
f11dsf.
The matrix
, and the preconditioning matrix
, are represented in coordinate storage (CS) format (see
Section 2.1.1 in the F11 Chapter Introduction) in the arrays
a,
irow and
icol, as returned from
f11dtf. The array
a holds the nonzero entries in these matrices, while
irow and
icol hold the corresponding row and column indices.
f11duf is a Black Box routine which calls
f11brf,
f11bsf and
f11btf. If you wish to use an alternative storage scheme, preconditioner, or termination criterion, or require additional diagnostic information, you should call these underlying routines directly.
4
References
Freund R W (1993) A transpose-free quasi-minimal residual algorithm for non-Hermitian linear systems SIAM J. Sci. Comput. 14 470–482
Freund R W and Nachtigal N (1991) QMR: a Quasi-Minimal Residual Method for Non-Hermitian Linear Systems Numer. Math. 60 315–339
Saad Y and Schultz M (1986) GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems SIAM J. Sci. Statist. Comput. 7 856–869
Sleijpen G L G and Fokkema D R (1993) BiCGSTAB for linear equations involving matrices with complex spectrum ETNA 1 11–32
Sonneveld P (1989) CGS, a fast Lanczos-type solver for nonsymmetric linear systems SIAM J. Sci. Statist. Comput. 10 36–52
Van der Vorst H (1989) Bi-CGSTAB, a fast and smoothly converging variant of Bi-CG for the solution of nonsymmetric linear systems SIAM J. Sci. Statist. Comput. 13 631–644
5
Arguments
- 1: – Character(*)Input
-
On entry: specifies the iterative method to be used.
- Restarted generalized minimum residual method.
- Conjugate gradient squared method.
- Bi-conjugate gradient stabilized () method.
- Transpose-free quasi-minimal residual method.
Constraint:
, , or .
- 2: – IntegerInput
- 3: – IntegerInput
- 4: – Complex (Kind=nag_wp) arrayInput
- 5: – IntegerInput
- 6: – Integer arrayInput
- 7: – Integer arrayInput
- 8: – IntegerInput
- 9: – Integer arrayInput
- 10: – Integer arrayInput
- 11: – IntegerInput
- 12: – Integer arrayInput
- 13: – Integer arrayInput
- 14: – Integer arrayInput
- 15: – Integer arrayInput
-
On entry: the values returned in arrays
a,
irow,
icol,
ipivp,
ipivq and
idiag by a previous call to
f11dtf.
The arrays
istb and
indb together with the scalars
n,
nnz,
la,
nb and
lindb must be the same values that were supplied in the preceding call to
f11dtf.
- 16: – Complex (Kind=nag_wp) arrayInput
-
On entry: the right-hand side vector .
- 17: – IntegerInput
-
On entry: if
,
m is the dimension of the restart subspace.
If
,
m is the order
of the polynomial Bi-CGSTAB method.
Otherwise,
m is not referenced.
Constraints:
- if , ;
- if , .
- 18: – Real (Kind=nag_wp)Input
-
On entry: the required tolerance. Let
denote the approximate solution at iteration
, and
the corresponding residual. The algorithm is considered to have converged at iteration
if
If
,
is used, where
is the
machine precision. Otherwise
is used.
Constraint:
.
- 19: – IntegerInput
-
On entry: the maximum number of iterations allowed.
Constraint:
.
- 20: – Complex (Kind=nag_wp) arrayInput/Output
-
On entry: an initial approximation to the solution vector .
On exit: an improved approximation to the solution vector .
- 21: – Real (Kind=nag_wp)Output
-
On exit: the final value of the residual norm
, where
is the output value of
itn.
- 22: – IntegerOutput
-
On exit: the number of iterations carried out.
- 23: – Complex (Kind=nag_wp) arrayWorkspace
- 24: – IntegerInput
-
On entry: the dimension of the array
work as declared in the (sub)program from which
f11duf is called.
Constraints:
- if , ;
- if , ;
- if , ;
- if , .
- 25: – IntegerInput/Output
-
On entry:
ifail must be set to
,
. If you are unfamiliar with this argument you should refer to
Section 3.4 in How to Use the NAG Library and its Documentation for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value
is recommended. If the output of error messages is undesirable, then the value
is recommended. Otherwise, if you are not familiar with this argument, the recommended value is
.
When the value is used it is essential to test the value of ifail on exit.
On exit:
unless the routine detects an error or a warning has been flagged (see
Section 6).
6
Error Indicators and Warnings
If on entry
or
, explanatory error messages are output on the current error message unit (as defined by
x04aaf).
Errors or warnings detected by the routine:
-
On entry, for , and .
Constraint: , for .
On entry, and .
Constraint: , for
On entry, .
Constraint: .
On entry, and .
Constraint: .
On entry, , and .
Constraint: .
On entry, .
Constraint: .
On entry, and .
Constraint: if , .
If , .
On entry, .
Constraint: .
On entry, .
Constraint: , or .
On entry, .
Constraint: .
On entry, and .
Constraint: .
On entry, .
Constraint: .
On entry, and .
Constraint: .
On entry, .
Constraint: .
-
On entry, element
of
a was out of order.
Check that
a,
irow,
icol,
ipivp,
ipivq,
istr and
idiag have not been corrupted between calls to
f11dtf and
f11duf.
On entry,
and
.
Constraint:
, for
.
Check that
a,
irow,
icol,
ipivp,
ipivq,
istr and
idiag have not been corrupted between calls to
f11dtf and
f11duf.
On entry,
and
.
Constraint:
, for
.
Check that
a,
irow,
icol,
ipivp,
ipivq,
istr and
idiag have not been corrupted between calls to
f11dtf and
f11duf.
On entry, location
of
was a duplicate.
Check that
a,
irow,
icol,
ipivp,
ipivq,
istr and
idiag have not been corrupted between calls to
f11dtf and
f11duf.
-
The CS representation of the preconditioner is invalid.
Check that
a,
irow,
icol,
ipivp,
ipivq,
istr and
idiag have not been corrupted between calls to
f11dtf and
f11duf.
-
The required accuracy could not be obtained. However, a reasonable accuracy may have been achieved.
You should check the output value of
rnorm for acceptability. This error code usually implies that your problem has been fully and satisfactorily solved to within or close to the accuracy available on your system. Further iterations are unlikely to improve on this situation.
-
The solution has not converged after iterations.
-
Algorithmic breakdown. A solution is returned, although it is possible that it is completely inaccurate.
An unexpected error has been triggered by this routine. Please
contact
NAG.
See
Section 3.9 in How to Use the NAG Library and its Documentation for further information.
Your licence key may have expired or may not have been installed correctly.
See
Section 3.8 in How to Use the NAG Library and its Documentation for further information.
Dynamic memory allocation failed.
See
Section 3.7 in How to Use the NAG Library and its Documentation for further information.
7
Accuracy
On successful termination, the final residual
, where
, satisfies the termination criterion
The value of the final residual norm is returned in
rnorm.
8
Parallelism and Performance
f11duf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f11duf 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.
The time taken by
f11duf for each iteration is roughly proportional to the value of
nnzc returned from the preceding call to
f11dtf.
The number of iterations required to achieve a prescribed accuracy cannot be easily determined a priori, as it can depend dramatically on the conditioning and spectrum of the preconditioned coefficient matrix .
10
Example
This example program reads in a sparse matrix
and a vector
. It calls
f11dtf, with the array
and the array
, to compute an overlapping incomplete
factorization. This is then used as an additive Schwarz preconditioner on a call to
f11duf which uses the RGMRES method to solve
.
10.1
Program Text
Program Text (f11dufe.f90)
10.2
Program Data
Program Data (f11dufe.d)
10.3
Program Results
Program Results (f11dufe.r)