Imsls provides iterative methods for sparse linear systems of equations.
Features
--------
* imsls_bicg: BIConjugate Gradient method
* imsls_bicgstab: BIConjugate Gradient STABilized method
* imsls_pcg: Conjugate Gradient method
* imsls_cgs: Conjugate Gradient Squared method
* imsls_cheby: CHEBYshev method
* imsls_gmres: Generalized Minimal RESidual method
* imsls_jacobi: JACOBI method
* imsls_qmr: Quasi Minimal Residual method
* imsls_sor: Successive Over-Relaxation method
Support:
* imsls_benchmatrix : Test a matrix against all solvers.
* imsls_getpath : Returns the path to the current module.
* imsls_lehmer : Returns the Lehmer matrix.
* imsls_makefish : Returns the Poisson matrix.
* imsls_matgen : Returns a test matrix.
* imsls_nonsym : Returns a non symetric matrix.
* imsls_spdiags : Extract and create sparse band and diagonal matrices
* imsls_split : Sets up the matrix splitting for Jacobi and SOR.
* imsls_tester : Test all algorithms
* imsls_wathen : Generates a random finite element matrix.
Compatibility:
* mtlb_bicg : Solves linear equations using BiConjugate Gradient Method with
preconditioning.
* mtlb_bicgstab : Solves linear equations using BiConjugate Gradient Stabilized
Method with preconditioning.
* mtlb_cgs : Solves linear equations using Conjugate Gradient Squared Method
with preconditioning.
* mtlb_gmres : Solves linear equations using Generalized Minimal residual with
restarts .
* mtlb_pcg : Solves linear equations using Conjugate Gradient method with
preconditioning.
* mtlb_qmr : Solves linear equations using Quasi Minimal Residual method with
preconditioning.
Bibliography
------------
* http://www.irisa.fr/aladin/codes/SCILIN/
* http://www.netlib.org/templates/
* http://graal.ens-lyon.fr/~jylexcel/scilab-sparse/meeting07/
