suitesparse 1:5.1.2~beta2-1 source package in Ubuntu

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The AMD library provides a set of routines for pre-ordering sparse matrices
 prior to Cholesky or LU factorization, using the "Approximate Minimum Degree
 ordering" algorithm.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The BTF library is a software package for permuting a matrix into Block upper
 Triangular Form. It includes a maximum transversal algorithm, which finds a
 permutation of a square or rectangular matrix so that it has a zero-free
 diagonal (if one exists); otherwise, it finds a maximal matching which
 maximizes the number of nonzeros on the diagonal. The package also includes a
 method for finding the strongly connected components of a graph. These two
 methods together give the permutation to block upper triangular form.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The CAMD library provides a set of routines for pre-ordering sparse matrices
 prior to Cholesky or LU factorization, using the approximate minimum degree
 ordering algorithm with optional ordering constraints.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The CCOLAMD library implements the "Constrained COLumn Approximate Minimum
 Degree ordering" algorithm. It computes a permutation vector P such that the
 LU factorization of A (:,P) tends to be sparser than that of A. The Cholesky
 factorization of (A (:,P))'*(A (:,P)) will also tend to be sparser than that
 of A'*A.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The CHOLMOD library provides a set of routines for factorizing sparse
 symmetric positive definite matrices of the form A or AA', updating/downdating
 a sparse Cholesky factorization, solving linear systems, updating/downdating
 the solution to the triangular system Lx=b, and many other sparse matrix
 functions for both symmetric and unsymmetric matrices. Its supernodal Cholesky
 factorization relies on LAPACK and the Level-3 BLAS, and obtains a substantial
 fraction of the peak performance of the BLAS.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The COLAMD library implements the "COLumn Approximate Minimum Degree ordering"
 algorithm. It computes a permutation vector P such that the LU factorization
 of A (:,P) tends to be sparser than that of A. The Cholesky factorization of
 (A (:,P))'*(A (:,P)) will also tend to be sparser than that of A'*A.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The CXSparse library provides several matrix algorithms. The focus is on direct
 methods; iterative methods and solvers for eigenvalue problems are beyond the
 scope of this package.
 .
 The performance of the sparse factorization methods in CXSparse will not be
 competitive with UMFPACK or CHOLMOD, but the codes are much more concise and
 easy to understand. Other methods are competitive.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 SuiteSparse:GraphBLAS is an full implementation of the GraphBLAS standard,
 which defines a set of sparse matrix operations on an extended algebra of
 semirings using an almost unlimited variety of operators and types. When
 applied to sparse adjacency matrices, these algebraic operations are
 equivalent to computations on graphs. GraphBLAS provides a powerful and
 expressive framework for creating graph algorithms based on the elegant
 mathematics of sparse matrix operations on a semiring.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The KLU library provides routines for LU factorization, primarily for circuit
 simulation.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The LDL library provides routines for sparse LDL' factorization and solving.
 These routines are not terrifically fast (they do not use dense matrix
 kernels), but the code is very short and concise. The purpose is to illustrate
 the algorithms in a very concise and readable manner, primarily for
 educational purposes.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 RBio is a library for reading/writing sparse matrices in the Rutherford/Boeing
 format.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 SuiteSparseQR (SPQR) is a multithreaded, multifrontal, rank-revealing sparse
 QR factorization method.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices. This package includes the following libraries:
 .
 AMD approximate minimum degree ordering
 .
 CAMD symmetric approximate minimum degree
 .
 BTF permutation to block triangular form (beta)
 .
 COLAMD column approximate minimum degree ordering
 .
 CCOLAMD constrained column approximate minimum degree ordering
 .
 CHOLMOD sparse Cholesky factorization
 .
 CXSparse a concise sparse matrix package
 .
 KLU sparse LU factorization, primarily for circuit simulation
 .
 LDL a simple LDL' factorization
 .
 UMFPACK sparse LU factorization
 .
 RBio read/write sparse matrices in Rutherford/Boeing format
 .
 SPQR sparse QR factorization
 .
 GraphBLAS graph algorithms via sparse matrix operations on semirings
 .
 SuiteSparse_config configuration routines for all the above packages.
 .
 This package contains the static libraries and header files.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices. This package contains the user guides for the
 libraries distributed by the SuiteSparse project.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The SuiteSparse_config library provides configuration routines that are common
 to all SuiteSparse libraries.

 Suitesparse is a collection of libraries for computations involving
 sparse matrices.
 .
 The UMFPACK library provides a set of routines solving sparse linear systems
 via LU factorization.