Integer, Intent (In)	::	n, la, irow(la), icol(la), istr(n+1)
Integer, Intent (Inout)	::	ipiv(n), ifail
Real (Kind=nag_wp), Intent (In)	::	a(la), y(n)
Real (Kind=nag_wp), Intent (Out)	::	x(n)
Character (1), Intent (In)	::	check

C Header Interface

#include <nag.h>

void	f11jbf_ (const Integer n, const double a[], const Integer la, const Integer irow[], const Integer icol[], Integer ipiv[], const Integer istr[], const char check, const double y[], double x[], Integer ifail, const Charlen length_check)

The routine may be called by the names f11jbf or nagf_sparse_real_symm_precon_ichol_solve.

3 Description

f11jbf solves a system of linear equations

M x = y

involving the preconditioning matrix

M = P L D L^{T} P^{T}

, corresponding to an incomplete Cholesky decomposition of a sparse symmetric matrix stored in symmetric coordinate storage (SCS) format (see Section 2.1.2 in the F11 Chapter Introduction), as generated by f11jaf.

In the above decomposition

L

is a lower triangular sparse matrix with unit diagonal,

D

is a diagonal matrix and

P

is a permutation matrix.

L

and

D

are supplied to f11jbf through the matrix

C = L + D^{- 1} - I

which is a lower triangular n by n sparse matrix, stored in SCS format, as returned by f11jaf. The permutation matrix

P

is returned from f11jaf via the array ipiv.

It is envisaged that a common use of f11jbf will be to carry out the preconditioning step required in the application of f11gef to sparse symmetric linear systems. f11jbf is used for this purpose by the Black Box routine f11jcf.

f11jbf may also be used in combination with f11jaf to solve a sparse symmetric positive definite system of linear equations directly (see Section 9.4 in f11jaf).

4 References

None.

5 Arguments

1: $n$ – Integer Input

On entry:

n

, the order of the matrix

M

. This must be the same value as was supplied in the preceding call to f11jaf.

Constraint:

n \geq 1

2: $a (la)$ – Real (Kind=nag_wp) array Input

On entry: the values returned in the array a by a previous call to f11jaf.

3: $la$ – Integer Input

On entry: the dimension of the arrays a, irow and icol as declared in the (sub)program from which f11jbf is called. This must be the same value returned by the preceding call to f11jaf.

4: $irow (la)$ – Integer array Input

5: $icol (la)$ – Integer array Input

6: $ipiv (n)$ – Integer array Input

7: $istr (n + 1)$ – Integer array Input

On entry: the values returned in arrays irow, icol, ipiv and istr by a previous call to f11jaf.

8: $check$ – Character(1) Input

On entry: specifies whether or not the input data should be checked.

$check ='C'$: Checks are carried out on the values of n, irow, icol, ipiv and istr.
$check ='N'$: No checks are carried out.

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, $check = ⟨ value ⟩$ .
Constraint: $check ='C'$ or $'N'$ .

$ifail = 2$: On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 1$ .

$ifail = 3$: On entry, $a (i)$ is out of order: $i = ⟨ value ⟩$ .

On entry, $I = ⟨ value ⟩$ , $icol (I) = ⟨ value ⟩$ and $irow (I) = ⟨ value ⟩$ .
Constraint: $icol (I) \geq 1$ and $icol (I) \leq irow (I)$ .

On entry, $i = ⟨ value ⟩$ , $ipiv (i) = ⟨ value ⟩$ , $n = ⟨ value ⟩$ .
Constraint: $ipiv (i) \geq 1$ and $ipiv (i) \leq n$ .

On entry, $i = ⟨ value ⟩$ , $irow (i) = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $irow (i) \geq 1$ and $irow (i) \leq n$ .

On entry, $ipiv (i)$ is a repeated value: $i = ⟨ value ⟩$ .

On entry, istr appears to be invalid.

On entry, $istr (i)$ is inconsistent with irow: $i = ⟨ value ⟩$ .

On entry, the location ( $irow (I), icol (I)$ ) is a duplicate: $I = ⟨ value ⟩$ .
Check that a, irow, icol, ipiv and istr have not been corrupted between calls to f11jaf and f11jbf.

$ifail = - 99$: 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 computed solution

x

is the exact solution of a perturbed system of equations

(M + δ M) x = y

, where

| δ M | \leq c (n) ε P | L | | D | | L^{T} | P^{T},

c (n)

is a modest linear function of

n

, and

ε

is the machine precision.

8 Parallelism and Performance

f11jbf is not threaded in any implementation.

9 Further Comments

9.1 Timing

The time taken for a call to f11jbf is proportional to the value of nnzc returned from f11jaf.

9.2 Use of check

It is expected that a common use of f11jbf will be to carry out the preconditioning step required in the application of f11gef to sparse symmetric linear systems. In this situation f11jbf is likely to be called many times with the same matrix

M

. In the interests of both reliability and efficiency, you are recommended to set

check ='C'

for the first of such calls, and to set

check ='N'

for all subsequent calls.

10 Example

This example reads in a symmetric positive definite sparse matrix

A

and a vector

y

. It then calls f11jaf, with

lfill = - 1

and

dtol = 0.0

, to compute the complete Cholesky decomposition of

A

A = P L D L^{T} P^{T} .

Then it calls f11jbf to solve the system

P L D L^{T} P^{T} x = y .

It then repeats the exercise for the same matrix permuted with the bandwidth-reducing Reverse Cuthill–McKee permutation, calculated with f11yef.

f11jb: FL CL CPP AD

NAG FL Interfacef11jbf (real_​symm_​precon_​ichol_​solve)

▸▿ Contents

1 Purpose

2 Specification