SlackBuilds Repository

15.0 > Academic > suitesparse (7.12.2)

suitesparse is a collection of libraries for computations involving
sparse matrices. The package includes the following libraries:

AMD: approximate minimum degree ordering.
CAMD: constrained approximate minimum degree ordering.
COLAMD: column approximate minimum degree ordering.
CCOLAMD: constrained column approximate minimum degree ordering.
CHOLMOD: sparse Cholesky factorization.
CXSparse: CSparse extended: complex matrix, int and long int support.
KLU & BTF: sparse LU factorization, primarily for circuit simulation.
LDL: a simple LDL^t factorization.
SQPR: a multithread, multifrontal, rank-revealing sparse QR
      factorization method.
UMFPACK: sparse LU factorization.
RBio: read/write files in Rutherford/Boeing format.
GraphBLAS: graph algorithms in the language of linear algebra
Mongoose: graph partitioning
ssget: MATLAB and Java interface to the SuiteSparse Matrix Collection

Suitesparse is an optional dependency for the octave package.

CXSparse is a superset of CSparse, and the two share common header
names, so it does not make sense to build both. CXSparse is built
by default.

CUDA support has been tested with SlackBuilds cudatoolkit_12 and
cudatoolkit_13. When building SuiteSparse, either of these CUDA
toolkits can be detected and used if already installed.

SlackBuilds.org also has all parts of this suite as individual builds.
However DO NOT install those individual builds as well as this suite;
choose one or the other.

This requires: lapack, OpenBLAS, cmake-opt

Maintained by: Christoph Willing
Keywords: octave,lapack,blas,sparce matrices
ChangeLog: suitesparse