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is a package for solving large sparse systems of linear equations
like those which arise from discretization of partial differential equations.
The primary aim of LASPack
is the implementation of efficient iterative
methods for the solution of systems of linear equations.
All routines and data structures are optimized for effective usage
of resources especially with regard to large sparse matrices.
The package can be accessed from an application through
a straightforward interface defined in the form of procedure calls.
Beside the obligatory Jacobi, succesive over-relaxation, Chebyshev, and
conjugate gradient solvers,
contains selected state-of-the-art algorithms
which are commonly used for large sparse systems:
All above solvers are applicable not only to the positive definite or
but are also adopted for singular systems
(e.g. arising from discretization of Neumann boundary value problems).
CG-like methods for non-symmetric systems: CGN, GMRES, BiCG, QMR, CGS, and
multilevel methods such as multigrid and conjugate gradient method
preconditioned by multigrid and BPX preconditioners.
The implementation is based on an object-oriented approach
(although it has been programmed in C).
Vectors and matrices are defined as new data types in connection with
the corresponding supporting routines.
The basic operations are implemented so
that they allow the programming of linear algebra algorithms
in a natural way.
is extensible in a simple manner.
An access to the internal representation of vectors and matrices
is not necessary and is,
as required of the object-oriented programming,
This allows an improvement of algorithms or a modification
of data structures with no adjustment of application programs
using the package.
is written in ANSI C and is thus largely portable.
Tomas Skalicky (firstname.lastname@example.org)