Provided by: librheolef-dev_7.1-1_amd64 
NAME
gmres - generalized minimum residual algorithm (rheolef-7.1)
SYNOPSIS
template <class Matrix, class Vector, class Preconditioner,
class SmallMatrix, class SmallVector>
int gmres (const Matrix &A, Vector &x, const Vector &b, const Preconditioner &M,
SmallMatrix &H, const SmallVector& V, const solver_option& sopt = solver_option())
EXAMPLE
solver_option sopt;
sopt.tol = 1e-7;
sopt.max_iter = 100;
size_t m = sopt.krylov_dimension = 6;
Eigen::Matrix<T,Eigen::Dynamic,Eigen::Dynamic> H(m+1,m+1);
Eigen::Matrix<T,Eigen::Dynamic,1> V(m);
int status = gmres (A, x, b, ilut(a), H, V, sopt);
DESCRIPTION
This function solves the unsymmetric linear system A*x=b with the generalized minimum
residual algorithm. The gmres function follows the algorithm described on p. 20 in
R. Barrett, M. Berry, T. F. Chan, J. Demmel, J. Donato,
J. Dongarra, V. Eijkhout, R. Pozo, C. Romine and H. Van der Vorst,
Templates for the solution of linear systems: building blocks for iterative methods,
SIAM, 1994.
The fourth argument of gmres is a preconditionner: here, the ilut(5) one is used, for
simplicity.
Next, H specifies a matrix to hold the coefficients of the upper Hessenberg matrix
constructed by the gmres iterations, m specifies the number of iterations for each
restart. We have used here the eigen dense matrix and vector types for the H and V
vectors, with sizes related to the Krylov space dimension m. Finally, the solver_option(4)
variable sopt transmits the stopping criterion with sopt.tol and sopt.max_iter.
On return, the sopt.residue and sopt.n_iter indicate the reached residue and the number of
iterations effectively performed. The return status is zero when the prescribed tolerance
tol has been obtained, and non-zero otherwise. Also, the x variable contains the
approximate solution. See also the solver_option(4) for more controls upon the stopping
criterion.
REMARKS
gmres requires two matrices as input: A and H. The A matrix, which will typically be
sparse, corresponds to the matrix involved in the linear system A*x=b. Conversely, the H
matrix, which will typically be dense, corresponds to the upper Hessenberg matrix that is
constructed during the gmres iterations. Within gmres, H is used in a different way than
A, so its class must supply different functionality. That is, A is only accessed though
its matrix-vector and transpose-matrix-vector multiplication functions. On the other hand,
gmres solves a dense upper triangular linear system of equations on H. Therefore, the
class to which H belongs must provide H(i,j) accessors.
It is important to remember that we use the convention that indices are 0-based. That is
H(0,0) is the first component of the matrix. Also, the type of the matrix must be
compatible with the type of single vector entry. That is, operations such as H(i,j)*x(j)
must be able to be carried out.
IMPLEMENTATION
This documentation has been generated from file linalg/lib/gmres.h
The present template implementation is inspired from the IML++ 1.2 iterative method
library, http://math.nist.gov/iml++
template <class Matrix, class Vector, class Preconditioner,
class SmallMatrix, class SmallVector>
int gmres (const Matrix &A, Vector &x, const Vector &b, const Preconditioner &M,
SmallMatrix &H, const SmallVector& V, const solver_option& sopt = solver_option())
{
typedef typename Vector::size_type Size;
typedef typename Vector::float_type Real;
std::string label = (sopt.label != "" ? sopt.label : "gmres");
Size m = sopt.krylov_dimension;
Vector w;
SmallVector s(m+1), cs(m+1), sn(m+1);
Real residue;
Real norm_b = norm(M.solve(b));
Vector r = M.solve(b - A * x);
Real beta = norm(r);
if (sopt.p_err) (*sopt.p_err) << "[" << label << "] # norm_b=" << norm_b << std::endl
<< "[" << label << "] #iteration residue" << std::endl;
if (sopt.absolute_stopping || norm_b == Real(0)) norm_b = 1;
sopt.n_iter = 0;
sopt.residue = norm(r)/norm_b;
if (sopt.residue <= sopt.tol) return 0;
std::vector<Vector> v (m+1);
for (sopt.n_iter = 1; sopt.n_iter <= sopt.max_iter; ) {
v[0] = r/beta;
for (Size i = 0; i < m+1; i++) s(i) = 0; // std::numeric_limits<Float>::max();
s(0) = beta;
for (Size i = 0; i < m && sopt.n_iter <= sopt.max_iter; i++, sopt.n_iter++) {
w = M.solve(A * v[i]);
for (Size k = 0; k <= i; k++) {
H(k, i) = dot(w, v[k]);
w -= H(k, i) * v[k];
}
H(i+1, i) = norm(w);
v[i+1] = w/H(i+1,i);
for (Size k = 0; k < i; k++) {
details::apply_plane_rotation (H(k,i), H(k+1,i), cs(k), sn(k));
}
details::generate_plane_rotation (H(i,i), H(i+1,i), cs(i), sn(i));
details::apply_plane_rotation (H(i,i), H(i+1,i), cs(i), sn(i));
details::apply_plane_rotation (s(i), s(i+1), cs(i), sn(i));
sopt.residue = abs(s(i+1))/norm_b;
if (sopt.p_err) (*sopt.p_err) << "[" << label << "] " << sopt.n_iter << " " << sopt.residue << std::endl;
if (sopt.residue <= sopt.tol) {
details::update (x, i, H, s, v);
return 0;
}
}
details::update (x, m - 1, H, s, v);
r = M.solve(b - A * x);
beta = norm(r);
sopt.residue = beta/norm_b;
if (sopt.p_err) (*sopt.p_err) << "[" << label << "] " << sopt.n_iter << " " << sopt.residue << std::endl;
if (sopt.residue < sopt.tol) return 0;
}
return 1;
}
template <class SmallMatrix, class SmallVector, class Vector, class Vector2, class Size>
void update (Vector& x, Size k, const SmallMatrix& h, const SmallVector& s, Vector2& v) {
SmallVector y = s;
// back solve:
for (int i = k; i >= 0; i--) {
y(i) /= h(i,i);
for (int j = i - 1; j >= 0; j--)
y(j) -= h(j,i) * y(i);
}
for (Size j = 0; j <= k; j++) {
x += v[j] * y(j);
}
}
template<class Real>
void generate_plane_rotation (const Real& dx, const Real& dy, Real& cs, Real& sn) {
if (dy == Real(0)) {
cs = 1.0;
sn = 0.0;
} else if (abs(dy) > abs(dx)) {
Real temp = dx / dy;
sn = 1.0 / sqrt( 1.0 + temp*temp );
cs = temp * sn;
} else {
Real temp = dy / dx;
cs = 1.0 / sqrt( 1.0 + temp*temp );
sn = temp * cs;
}
}
template<class Real>
void apply_plane_rotation (Real& dx, Real& dy, const Real& cs, const Real& sn) {
Real temp = cs * dx + sn * dy;
dy = -sn * dx + cs * dy;
dx = temp;
}
AUTHOR
Pierre Saramito <Pierre.Saramito@imag.fr>
COPYRIGHT
Copyright (C) 2000-2018 Pierre Saramito <Pierre.Saramito@imag.fr> GPLv3+: GNU GPL
version 3 or later <http://gnu.org/licenses/gpl.html>. This is free software: you
are free to change and redistribute it. There is NO WARRANTY, to the extent permitted by
law.