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gmres
Generalized Minimum RESidual method
Calling Sequence
[x,flag,err,iter,res] = gmres(A,b,[rstr,[tol,[maxi,[M,[x0]]]]])
Arguments
- A
n-by-n matrix or function returning
A*x
. IfA
is a function, it must have the following header :function y=A(x)
- b
right hand side vector
- x0
initial guess vector (default: zeros(n,1))
- M
preconditioner: matrix of size n-by-n or function returning
M*x
(In the first case, default: eye(n,n)). If M is a function, it must have the following header :function y=M(x)
- rstr
number of iterations between restarts (default: 10)
- maxi
maximum number of iterations (default: n)
- tol
error tolerance (default: 1e-6)
- x
solution vector
- err
final residual norm
- iter
number of iterations performed
- flag
- 0 =
gmres
converged to the desired tolerance withinmaxi
iterations- 1 =
no convergence given
maxi
- res
residual vector
Description
- GMRES
solves the linear system
Ax=b
using the Generalized Minimal residual method with restarts.- Details
of this algorithm are described in :
"Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods", Barrett, Berry, Chan, Demmel, Donato, Dongarra, Eijkhout, Pozo, Romine, and Van der Vorst, SIAM Publications, 1993 (ftp netlib2.cs.utk.edu; cd linalg; get templates.ps).
"Iterative Methods for Sparse Linear Systems, Second Edition" Saad, SIAM Publications, 2003 (ftp ftp.cs.umn.edu; cd dept/users/saad/PS; get all_ps.zip).
Examples
// If A and M are matrices A=[ 94 0 0 0 0 28 0 0 32 0 0 59 13 5 0 0 0 10 0 0 0 13 72 34 2 0 0 0 0 65 0 5 34 114 0 0 0 0 0 55 0 0 2 0 70 0 28 32 12 0 28 0 0 0 0 87 20 0 33 0 0 0 0 0 28 20 71 39 0 0 0 10 0 0 32 0 39 46 8 0 32 0 0 0 12 33 0 8 82 11 0 0 65 55 0 0 0 0 11 100]; b=ones(10,1); [x,flag,err,iter,res] = gmres(A, b) M = eye(10, 10); [x,flag,err,iter,res] = gmres(A, b, 10, 1d-12, 20, M, zeros(10, 1)) // If A is a matrix and M is a function A=[ 94 0 0 0 0 28 0 0 32 0 0 59 13 5 0 0 0 10 0 0 0 13 72 34 2 0 0 0 0 65 0 5 34 114 0 0 0 0 0 55 0 0 2 0 70 0 28 32 12 0 28 0 0 0 0 87 20 0 33 0 0 0 0 0 28 20 71 39 0 0 0 10 0 0 32 0 39 46 8 0 32 0 0 0 12 33 0 8 82 11 0 0 65 55 0 0 0 0 11 100]; b=ones(10,1); function y=Mtimesx(x) M = eye(10,10); y = M*x; endfunction [x,flag,err,iter,res] = gmres(A, b, 10, 1d-12, 20, Mtimesx, zeros(10, 1)) // If A is a function and M is a matrix function y=Atimesx(x) A=[ 94 0 0 0 0 28 0 0 32 0 0 59 13 5 0 0 0 10 0 0 0 13 72 34 2 0 0 0 0 65 0 5 34 114 0 0 0 0 0 55 0 0 2 0 70 0 28 32 12 0 28 0 0 0 0 87 20 0 33 0 0 0 0 0 28 20 71 39 0 0 0 10 0 0 32 0 39 46 8 0 32 0 0 0 12 33 0 8 82 11 0 0 65 55 0 0 0 0 11 100]; y = A * x; endfunction b = ones(10,1); M = eye(10, 10); [x,flag,err,iter,res] = gmres(Atimesx, b) [x,flag,err,iter,res] = gmres(Atimesx, b, 10, 1d-12, 20, M, zeros(10,1)) // If A and M are functions function y=Atimesx(x) A=[ 94 0 0 0 0 28 0 0 32 0 0 59 13 5 0 0 0 10 0 0 0 13 72 34 2 0 0 0 0 65 0 5 34 114 0 0 0 0 0 55 0 0 2 0 70 0 28 32 12 0 28 0 0 0 0 87 20 0 33 0 0 0 0 0 28 20 71 39 0 0 0 10 0 0 32 0 39 46 8 0 32 0 0 0 12 33 0 8 82 11 0 0 65 55 0 0 0 0 11 100]; y = A * x; endfunction function y=Mtimesx(x) M = eye(10,10); y = M*x; endfunction [x,flag,err,iter,res] = gmres(Atimesx, b, 10, 1d-12, 20, Mtimesx, zeros(10,1))
See Also
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