# NAG FL Interfacef11dqf (complex_​gen_​solve_​ilu)

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## 1Purpose

f11dqf 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 incomplete $LU$ preconditioning.

## 2Specification

Fortran Interface
 Subroutine f11dqf ( n, nnz, a, la, irow, icol, istr, b, m, tol, x, itn, work,
 Integer, Intent (In) :: n, nnz, la, irow(la), icol(la), istr(n+1), idiag(n), m, maxitn, lwork Integer, Intent (Inout) :: ipivp(n), ipivq(n), 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
#include <nag.h>
 void f11dqf_ (const char *method, const Integer *n, const Integer *nnz, const Complex a[], const Integer *la, const Integer irow[], const Integer icol[], 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)
The routine may be called by the names f11dqf or nagf_sparse_complex_gen_solve_ilu.

## 3Description

f11dqf solves a complex sparse non-Hermitian linear system of equations
 $Ax=b,$
using a preconditioned RGMRES (see Saad and Schultz (1986)), CGS (see Sonneveld (1989)), Bi-CGSTAB($\ell$) (see Van der Vorst (1989) and Sleijpen and Fokkema (1993)), or TFQMR (see Freund and Nachtigal (1991) and Freund (1993)) method.
f11dqf uses the incomplete $LU$ factorization determined by f11dnf as the preconditioning matrix. A call to f11dqf must always be preceded by a call to f11dnf. Alternative preconditioners for the same storage scheme are available by calling f11dsf.
The matrix $A$, and the preconditioning matrix $M$, 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 f11dnf. The array a holds the nonzero entries in these matrices, while irow and icol hold the corresponding row and column indices.
f11dqf 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.

## 4References

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$\left(\ell \right)$ 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

## 5Arguments

1: $\mathbf{method}$Character(*) Input
On entry: specifies the iterative method to be used.
${\mathbf{method}}=\text{'RGMRES'}$
Restarted generalized minimum residual method.
${\mathbf{method}}=\text{'CGS'}$
${\mathbf{method}}=\text{'BICGSTAB'}$
Bi-conjugate gradient stabilized ($\ell$) method.
${\mathbf{method}}=\text{'TFQMR'}$
Transpose-free quasi-minimal residual method.
Constraint: ${\mathbf{method}}=\text{'RGMRES'}$, $\text{'CGS'}$, $\text{'BICGSTAB'}$ or $\text{'TFQMR'}$.
2: $\mathbf{n}$Integer Input
On entry: $n$, the order of the matrix $A$. This must be the same value as was supplied in the preceding call to f11dnf.
Constraint: ${\mathbf{n}}\ge 1$.
3: $\mathbf{nnz}$Integer Input
On entry: the number of nonzero elements in the matrix $A$. This must be the same value as was supplied in the preceding call to f11dnf.
Constraint: $1\le {\mathbf{nnz}}\le {{\mathbf{n}}}^{2}$.
4: $\mathbf{a}\left({\mathbf{la}}\right)$Complex (Kind=nag_wp) array Input
On entry: the values returned in the array a by a previous call to f11dnf.
5: $\mathbf{la}$Integer Input
On entry: the dimension of the arrays a, irow and icol as declared in the (sub)program from which f11dqf is called. This must be the same value as was supplied in the preceding call to f11dnf.
Constraint: ${\mathbf{la}}\ge 2×{\mathbf{nnz}}$.
6: $\mathbf{irow}\left({\mathbf{la}}\right)$Integer array Input
7: $\mathbf{icol}\left({\mathbf{la}}\right)$Integer array Input
8: $\mathbf{ipivp}\left({\mathbf{n}}\right)$Integer array Input
9: $\mathbf{ipivq}\left({\mathbf{n}}\right)$Integer array Input
10: $\mathbf{istr}\left({\mathbf{n}}+1\right)$Integer array Input
11: $\mathbf{idiag}\left({\mathbf{n}}\right)$Integer array Input
On entry: the values returned in arrays irow, icol, ipivp, ipivq, istr and idiag by a previous call to f11dnf.
ipivp and ipivq are restored on exit.
12: $\mathbf{b}\left({\mathbf{n}}\right)$Complex (Kind=nag_wp) array Input
On entry: the right-hand side vector $b$.
13: $\mathbf{m}$Integer Input
On entry: if ${\mathbf{method}}=\text{'RGMRES'}$, m is the dimension of the restart subspace.
If ${\mathbf{method}}=\text{'BICGSTAB'}$, m is the order $\ell$ of the polynomial Bi-CGSTAB method.
Otherwise, m is not referenced.
Constraints:
• if ${\mathbf{method}}=\text{'RGMRES'}$, $0<{\mathbf{m}}\le \mathrm{min}\phantom{\rule{0.125em}{0ex}}\left({\mathbf{n}},50\right)$;
• if ${\mathbf{method}}=\text{'BICGSTAB'}$, $0<{\mathbf{m}}\le \mathrm{min}\phantom{\rule{0.125em}{0ex}}\left({\mathbf{n}},10\right)$.
14: $\mathbf{tol}$Real (Kind=nag_wp) Input
On entry: the required tolerance. Let ${x}_{k}$ denote the approximate solution at iteration $k$, and ${r}_{k}$ the corresponding residual. The algorithm is considered to have converged at iteration $k$ if
 $‖rk‖∞≤τ×(‖b‖∞+‖A‖∞‖xk‖∞).$
If ${\mathbf{tol}}\le 0.0$, $\tau =\mathrm{max}\phantom{\rule{0.25em}{0ex}}\sqrt{\epsilon },10\epsilon ,\sqrt{n}\epsilon$ is used, where $\epsilon$ is the machine precision. Otherwise $\tau =\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left({\mathbf{tol}},10\epsilon ,\sqrt{n}\epsilon \right)$ is used.
Constraint: ${\mathbf{tol}}<1.0$.
15: $\mathbf{maxitn}$Integer Input
On entry: the maximum number of iterations allowed.
Constraint: ${\mathbf{maxitn}}\ge 1$.
16: $\mathbf{x}\left({\mathbf{n}}\right)$Complex (Kind=nag_wp) array Input/Output
On entry: an initial approximation to the solution vector $x$.
On exit: an improved approximation to the solution vector $x$.
17: $\mathbf{rnorm}$Real (Kind=nag_wp) Output
On exit: the final value of the residual norm ${‖{r}_{k}‖}_{\infty }$, where $k$ is the output value of itn.
18: $\mathbf{itn}$Integer Output
On exit: the number of iterations carried out.
19: $\mathbf{work}\left({\mathbf{lwork}}\right)$Complex (Kind=nag_wp) array Workspace
20: $\mathbf{lwork}$Integer Input
On entry: the dimension of the array work as declared in the (sub)program from which f11dqf is called.
Constraints:
• if ${\mathbf{method}}=\text{'RGMRES'}$, ${\mathbf{lwork}}\ge 4×{\mathbf{n}}+{\mathbf{m}}×\left({\mathbf{m}}+{\mathbf{n}}+5\right)+121$;
• if ${\mathbf{method}}=\text{'CGS'}$, ${\mathbf{lwork}}\ge 8×{\mathbf{n}}+120$;
• if ${\mathbf{method}}=\text{'BICGSTAB'}$, ${\mathbf{lwork}}\ge 2×{\mathbf{n}}×\left({\mathbf{m}}+3\right)+{\mathbf{m}}×\left({\mathbf{m}}+2\right)+120$;
• if ${\mathbf{method}}=\text{'TFQMR'}$, ${\mathbf{lwork}}\ge 11×{\mathbf{n}}+120$.
21: $\mathbf{ifail}$Integer Input/Output
On entry: ifail must be set to $0$, $-1$ or $1$ 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 $-1$ or $1$ is recommended. If message printing is undesirable, then the value $1$ is recommended. Otherwise, the value $0$ is recommended. When the value $-\mathbf{1}$ or $\mathbf{1}$ is used it is essential to test the value of ifail on exit.
On exit: ${\mathbf{ifail}}={\mathbf{0}}$ unless the routine detects an error or a warning has been flagged (see Section 6).

## 6Error Indicators and Warnings

If on entry ${\mathbf{ifail}}=0$ or $-1$, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
${\mathbf{ifail}}=1$
On entry, ${\mathbf{la}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{nnz}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{la}}\ge 2×{\mathbf{nnz}}$.
On entry, lwork is too small: ${\mathbf{lwork}}=⟨\mathit{\text{value}}⟩$. Minimum required value of ${\mathbf{lwork}}=⟨\mathit{\text{value}}⟩$.
On entry, ${\mathbf{m}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{m}}\ge 1$ and ${\mathbf{m}}\le \mathrm{min}\phantom{\rule{0.125em}{0ex}}\left({\mathbf{n}},⟨\mathit{\text{value}}⟩\right)$.
On entry, ${\mathbf{maxitn}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{maxitn}}\ge 1$.
On entry, ${\mathbf{method}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{method}}=\text{'RGMRES'}$, $\text{'CGS'}$ or $\text{'BICGSTAB'}$.
On entry, ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{n}}\ge 1$.
On entry, ${\mathbf{nnz}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{nnz}}\ge 1$.
On entry, ${\mathbf{nnz}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{nnz}}\le {{\mathbf{n}}}^{2}$.
On entry, ${\mathbf{tol}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{tol}}<1.0$.
${\mathbf{ifail}}=2$
On entry, ${\mathbf{a}}\left(i\right)$ is out of order: $i=⟨\mathit{\text{value}}⟩$.
On entry, $i=⟨\mathit{\text{value}}⟩$, ${\mathbf{icol}}\left(i\right)=⟨\mathit{\text{value}}⟩$, and ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{icol}}\left(i\right)\ge 1$ and ${\mathbf{icol}}\left(i\right)\le {\mathbf{n}}$.
On entry, $i=⟨\mathit{\text{value}}⟩$, ${\mathbf{irow}}\left(i\right)=⟨\mathit{\text{value}}⟩$, ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{irow}}\left(i\right)\ge 1$ and ${\mathbf{irow}}\left(i\right)\le {\mathbf{n}}$.
On entry, the location (${\mathbf{irow}}\left(i\right),{\mathbf{icol}}\left(i\right)$) is a duplicate: $i=⟨\mathit{\text{value}}⟩$.
Check that a, irow, icol, ipivp, ipivq, istr and idiag have not been corrupted between calls to f11dqf and f11dnf.
${\mathbf{ifail}}=3$
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 f11dnf and f11dqf.
${\mathbf{ifail}}=4$
The required accuracy could not be obtained. However, a reasonable accuracy may have been achieved.
${\mathbf{ifail}}=5$
The solution has not converged after $⟨\mathit{\text{value}}⟩$ iterations.
${\mathbf{ifail}}=6$
Algorithmic breakdown. A solution is returned, although it is possible that it is completely inaccurate.
${\mathbf{ifail}}=7$
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
A serious error, code $⟨\mathit{\text{value}}⟩$, has occurred in an internal call. Check all subroutine calls and array sizes. Seek expert help.
${\mathbf{ifail}}=-99$
See Section 7 in the Introduction to the NAG Library FL Interface for further information.
${\mathbf{ifail}}=-399$
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.
${\mathbf{ifail}}=-999$
Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

## 7Accuracy

On successful termination, the final residual ${r}_{k}=b-A{x}_{k}$, where $k={\mathbf{itn}}$, satisfies the termination criterion
 $‖rk‖∞≤τ×(‖b‖∞+‖A‖∞‖xk‖∞).$
The value of the final residual norm is returned in rnorm.

## 8Parallelism and Performance

f11dqf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f11dqf 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 f11dqf for each iteration is roughly proportional to the value of nnzc returned from the preceding call to f11dnf.
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 $\overline{A}={M}^{-1}A$.

## 10Example

This example solves a complex sparse non-Hermitian linear system of equations using the CGS method, with incomplete $LU$ preconditioning.

### 10.1Program Text

Program Text (f11dqfe.f90)

### 10.2Program Data

Program Data (f11dqfe.d)

### 10.3Program Results

Program Results (f11dqfe.r)