nag_sparse_herm_chol_sol (f11jqc) (PDF version)
f11 Chapter Contents
f11 Chapter Introduction
NAG C Library Manual

NAG Library Function Document

nag_sparse_herm_chol_sol (f11jqc)

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_sparse_herm_chol_sol (f11jqc) solves a complex sparse Hermitian system of linear equations, represented in symmetric coordinate storage format, using a conjugate gradient or Lanczos method, with incomplete Cholesky preconditioning.

2  Specification

#include <nag.h>
#include <nagf11.h>
void  nag_sparse_herm_chol_sol (Nag_SparseSym_Method method, Integer n, Integer nnz, const Complex a[], Integer la, const Integer irow[], const Integer icol[], const Integer ipiv[], const Integer istr[], const Complex b[], double tol, Integer maxitn, Complex x[], double *rnorm, Integer *itn, NagError *fail)

3  Description

nag_sparse_herm_chol_sol (f11jqc) solves a complex sparse Hermitian linear system of equations
Ax=b,
using a preconditioned conjugate gradient method (see Meijerink and Van der Vorst (1977)), or a preconditioned Lanczos method based on the algorithm SYMMLQ (see Paige and Saunders (1975)). The conjugate gradient method is more efficient if A is positive definite, but may fail to converge for indefinite matrices. In this case the Lanczos method should be used instead. For further details see Barrett et al. (1994).
nag_sparse_herm_chol_sol (f11jqc) uses the incomplete Cholesky factorization determined by nag_sparse_herm_chol_fac (f11jnc) as the preconditioning matrix. A call to nag_sparse_herm_chol_sol (f11jqc) must always be preceded by a call to nag_sparse_herm_chol_fac (f11jnc). Alternative preconditioners for the same storage scheme are available by calling nag_sparse_herm_sol (f11jsc).
The matrix A and the preconditioning matrix M are represented in symmetric coordinate storage (SCS) format (see Section 2.1.2 in the f11 Chapter Introduction) in the arrays a, irow and icol, as returned from nag_sparse_herm_chol_fac (f11jnc). The array a holds the nonzero entries in the lower triangular parts of these matrices, while irow and icol hold the corresponding row and column indices.

4  References

Barrett R, Berry M, Chan T F, Demmel J, Donato J, Dongarra J, Eijkhout V, Pozo R, Romine C and Van der Vorst H (1994) Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods SIAM, Philadelphia
Meijerink J and Van der Vorst H (1977) An iterative solution method for linear systems of which the coefficient matrix is a symmetric M-matrix Math. Comput. 31 148–162
Paige C C and Saunders M A (1975) Solution of sparse indefinite systems of linear equations SIAM J. Numer. Anal. 12 617–629

5  Arguments

1:     methodNag_SparseSym_MethodInput
On entry: specifies the iterative method to be used.
method=Nag_SparseSym_CG
Conjugate gradient method.
method=Nag_SparseSym_SYMMLQ
Lanczos method (SYMMLQ).
Constraint: method=Nag_SparseSym_CG or Nag_SparseSym_SYMMLQ.
2:     nIntegerInput
On entry: n, the order of the matrix A. This must be the same value as was supplied in the preceding call to nag_sparse_herm_chol_fac (f11jnc).
Constraint: n1.
3:     nnzIntegerInput
On entry: the number of nonzero elements in the lower triangular part of the matrix A. This must be the same value as was supplied in the preceding call to nag_sparse_herm_chol_fac (f11jnc).
Constraint: 1nnzn×n+1/2.
4:     a[la]const ComplexInput
On entry: the values returned in the array a by a previous call to nag_sparse_herm_chol_fac (f11jnc).
5:     laIntegerInput
On entry: the dimension of the arrays a, irow and icol. This must be the same value as was supplied in the preceding call to nag_sparse_herm_chol_fac (f11jnc).
Constraint: la2×nnz.
6:     irow[la]const IntegerInput
7:     icol[la]const IntegerInput
8:     ipiv[n]const IntegerInput
9:     istr[n+1]const IntegerInput
On entry: the values returned in arrays irow, icol, ipiv and istr by a previous call to nag_sparse_herm_chol_fac (f11jnc).
10:   b[n]const ComplexInput
On entry: the right-hand side vector b.
11:   toldoubleInput
On entry: the required tolerance. Let xk denote the approximate solution at iteration k, and rk the corresponding residual. The algorithm is considered to have converged at iteration k if
rkτ×b+Axk.
If tol0.0, τ=maxε,nε is used, where ε is the machine precision. Otherwise τ=maxtol,10ε,nε is used.
Constraint: tol<1.0.
12:   maxitnIntegerInput
On entry: the maximum number of iterations allowed.
Constraint: maxitn1.
13:   x[n]ComplexInput/Output
On entry: an initial approximation to the solution vector x.
On exit: an improved approximation to the solution vector x.
14:   rnormdouble *Output
On exit: the final value of the residual norm rk, where k is the output value of itn.
15:   itnInteger *Output
On exit: the number of iterations carried out.
16:   failNagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

NE_ACCURACY
The required accuracy could not be obtained. However a reasonable accuracy has been achieved.
NE_ALLOC_FAIL
Dynamic memory allocation failed.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_COEFF_NOT_POS_DEF
The matrix of the coefficients a appears not to be positive definite. The computation cannot continue.
NE_CONVERGENCE
The solution has not converged after value iterations.
NE_INT
On entry, maxitn=value.
Constraint: maxitn1.
On entry, n=value.
Constraint: n1.
On entry, nnz=value.
Constraint: nnz1.
NE_INT_2
On entry, la=value and nnz=value.
Constraint: la2×nnz.
On entry, nnz=value and n=value.
Constraint: nnzn×n+1/2.
NE_INTERNAL_ERROR
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 value, has occurred in an internal call to nag_sparse_herm_basic_solver (f11gsc). Check all function calls and array sizes. Seek expert help.
A serious error, code value, has occurred in an internal call to value. Check all function calls and array sizes. Seek expert help.
NE_INVALID_SCS
On entry, i=value, icol[i-1]=value, irow[i-1]=value.
Constraint: icol[i-1]1 and icol[i-1]irow[i-1].
Check that a, irow, icol, ipiv and istr have not been corrupted between calls to nag_sparse_herm_chol_fac (f11jnc) and nag_sparse_herm_chol_sol (f11jqc).
On entry, i=value, irow[i-1]=value and n=value.
Constraint: irow[i-1]1 and irow[i-1]n.
Check that a, irow, icol, ipiv and istr have not been corrupted between calls to nag_sparse_herm_chol_fac (f11jnc) and nag_sparse_herm_chol_sol (f11jqc).
NE_INVALID_SCS_PRECOND
The SCS representation of the preconditioner is invalid. Check that a, irow, icol, ipiv and istr have not been corrupted between calls to nag_sparse_herm_chol_fac (f11jnc) and nag_sparse_herm_chol_sol (f11jqc).
NE_NOT_STRICTLY_INCREASING
On entry, a[i-1] is out of order: i=value. Check that a, irow, icol, ipiv and istr have not been corrupted between calls to nag_sparse_herm_chol_fac (f11jnc) and nag_sparse_herm_chol_sol (f11jqc).
On entry, the location (irow[i-1],icol[i-1]) is a duplicate: i=value. Check that a, irow, icol, ipiv and istr have not been corrupted between calls to nag_sparse_herm_chol_fac (f11jnc) and nag_sparse_herm_chol_sol (f11jqc).
NE_PRECOND_NOT_POS_DEF
The preconditioner appears not to be positive definite. The computation cannot continue.
NE_REAL
On entry, tol=value.
Constraint: tol<1.0.

7  Accuracy

On successful termination, the final residual rk=b-Axk, where k=itn, satisfies the termination criterion
rkτ×b+Axk.
The value of the final residual norm is returned in rnorm.

8  Further Comments

The time taken by nag_sparse_herm_chol_sol (f11jqc) for each iteration is roughly proportional to the value of nnzc returned from the preceding call to nag_sparse_herm_chol_fac (f11jnc). One iteration with the Lanczos method (SYMMLQ) requires a slightly larger number of operations than one iteration with the conjugate gradient method.
The number of iterations required to achieve a prescribed accuracy cannot easily be determined a priori, as it can depend dramatically on the conditioning and spectrum of the preconditioned matrix of the coefficients A-=M-1A.

9  Example

This example solves a complex sparse Hermitian positive definite system of equations using the conjugate gradient method, with incomplete Cholesky preconditioning.

9.1  Program Text

Program Text (f11jqce.c)

9.2  Program Data

Program Data (f11jqce.d)

9.3  Program Results

Program Results (f11jqce.r)


nag_sparse_herm_chol_sol (f11jqc) (PDF version)
f11 Chapter Contents
f11 Chapter Introduction
NAG C Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2012