OOF2: The Manual
Name
GMRES (GMRESSolver) — Generalized Minimal Residual method. An iterative method for non-symmetric matrices.
Synopsis
GMRESSolver(max_iterations,krylov_dimension,tolerance,preconditioner)
Details
-
Base class:
LinearSolverPtr -
Parameters:
max_iterations- maximum number of iterations to perform Type: Integer.
krylov_dimension- Making the Krylov dimension bigger will improve convergence but use more memory. Type: Integer.
tolerance- largest acceptable relative error Type: A real number.
preconditioner- Black magic for making the matrix more easily solvable Type: An object of the
Preconditionerclass.
Description
The GMRESSolver solver implements the
preconditioned Generalized Minimal Residual
method for solving linear matrix equations. The matrix does not
have to be symmetric.
GMRES is an iterative method, meaning that
it creates an approximate solution and improves it on each
iteration. The iteration will cease when the relative error of
the solution is less than the given tolerance.
The solver will stop and report an error if the tolerance isn't
satisfied within max_iterations iterations.
GMRES (and other Krylov space methods) work by searching
for a solution in a subspace of the full vector space.[25]
The dimension of this subspace is given by the
krylov_dimension parameter. Using a larger
krylov_dimension will improve the convergence of
the method, but will require more memory.
The preconditioner parameter specifies which
Preconditioner to use, if any.
Preconditioners
speed the convergence of iterative methods by replacing the
original matrix by something closer to the identity matrix.
[25]
If
is an
initial guess for the solution of
,
then the initial residual is
.
The Krylov space of dimension
is spanned by the
vectors
.
GMRES finds the best solution in this space, and then restarts
with a new
.
If
is large
enough, fewer restarts are required, but more data must be retained.
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