Gentoo Packages

sci-libs/suitesparse (gentoo)

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Install

Install this package:

emerge -a sci-libs/suitesparse

Package Information

Description:
SuiteSparse is a suite of sparse matrix libraries from University of Florida Computer Science Department. Currently, this includes: * AMD: symmetric approximate minimum degree * BTF: permutation to block triangular form * CAMD: symmetric approximate minimum degree * CCOLAMD: constrained column approximate minimum degree * COLAMD: column approximate minimum degree * CHOLMOD: sparse supernodal Cholesky factorization and update/downdate * CSparse: a concise sparse matrix package * CXSparse: an extended version of CSparse * KLU: sparse LU factorization, for circuit simulation * LDL: a simple LDL^T factorization * SPQR: multifrontal sparse QT factorization * UMFPACK: sparse multifrontal LU factorization * SuiteSparse_config: common configuration for all but CSparse The Gentoo package does not include the suitesparse MATLAB tools from upstream, from the packages above and the following MATLAB-only packages: * RBio: MATLAB toolbox for reading/writing sparse matrices * LINFACTOR: solve Ax=b using LU or CHOL * MESHND: 2D and 3D mesh generation and nested dissection * SSMULT: sparse matrix times sparse matrix
Homepage:
https://people.engr.tamu.edu/davis/suitesparse.html
License:
metapackage

Versions

Version EAPI Keywords Slot
7.12.2 8 ~amd64 ~arm64 ~hppa ~ppc ~ppc64 ~sparc ~x86 0
5.4.0 7 amd64 arm64 ~hppa ~ppc ppc64 ~sparc ~x86 0

Metadata

Description

Maintainers

Raw Metadata XML 
<pkgmetadata>
	<maintainer type="project">
		<email>sci@gentoo.org</email>
		<name>Gentoo Science Project</name>
	</maintainer>
	<longdescription lang="en">
  SuiteSparse is a suite of sparse matrix libraries from University of
  Florida Computer Science Department. Currently, this includes:
    * AMD: symmetric approximate minimum degree
    * BTF: permutation to block triangular form
    * CAMD: symmetric approximate minimum degree
    * CCOLAMD: constrained column approximate minimum degree
    * COLAMD: column approximate minimum degree
    * CHOLMOD: sparse supernodal Cholesky factorization and update/downdate
    * CSparse: a concise sparse matrix package
    * CXSparse: an extended version of CSparse
    * KLU: sparse LU factorization, for circuit simulation
    * LDL: a simple LDL^T factorization
    * SPQR: multifrontal sparse QT factorization
    * UMFPACK: sparse multifrontal LU factorization
    * SuiteSparse_config: common configuration for all but CSparse
  The Gentoo package does not include the suitesparse MATLAB tools from
  upstream, from the packages above and the following MATLAB-only packages:
    * RBio: MATLAB toolbox for reading/writing sparse matrices
    * LINFACTOR: solve Ax=b using LU or CHOL
    * MESHND: 2D and 3D mesh generation and nested dissection
    * SSMULT: sparse matrix times sparse matrix
</longdescription>
	<use>
		<flag name="partition">
    Enable graph partitioning and graph-partition-based orderings
    through <pkg>sci-libs/metis</pkg> or <pkg>sci-libs/parmetis</pkg>
  </flag>
		<flag name="tbb">
    Enable multithreading with the Intel Threads Building Block
    <pkg>dev-cpp/tbb</pkg>
  </flag>
	</use>
</pkgmetadata>

Lint Warnings

USE Flags

Manage flags for this package: euse -i <flag> -p sci-libs/suitesparse | euse -E <flag> -p sci-libs/suitesparse | euse -D <flag> -p sci-libs/suitesparse

Flag Description 7.12.2 5.4.0
cuda Enable NVIDIA CUDA support (computation on GPU) ✓ ✓
doc Add extra documentation (API, Javadoc, etc). It is recommended to enable per package instead of globally ✓ ✓
lapack Add support for the virtual/lapack numerical library ✗ ✓
openmp Build support for the OpenMP (support parallel computing), requires >=sys-devel/gcc-4.2 built with USE="openmp" ✓ ✗
partition Enable graph partitioning and graph-partition-based orderings through <pkg>sci-libs/metis</pkg> or <pkg>sci-libs/parmetis</pkg> ✓ ✓
tbb Enable multithreading with the Intel Threads Building Block <pkg>dev-cpp/tbb</pkg> ✗ ✓