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Install

Install this package:

emerge -a sci-libs/suitesparse

If the package is masked, you can unmask it using the autounmask tool or standard emerge options:

autounmask sci-libs/suitesparse

Or alternatively:

emerge --autounmask-write -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
5.4.0	7	amd64 arm64 ~hppa ~ppc ppc64 ~sparc ~x86	0

Metadata

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

Maintainers

Gentoo Science Project (sci@gentoo.org) - Type: project

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

[Warning] USE flag 'cuda' in ebuild 5.4.0 is not documented in metadata.xml
[Warning] USE flag 'doc' in ebuild 5.4.0 is not documented in metadata.xml
[Warning] USE flag 'lapack' in ebuild 5.4.0 is not documented in metadata.xml
[Error] Missing md5-cache for ebuild suitesparse-5.4.0
[Error] Missing or unparsable Manifest file

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	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	✓
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>	✓

sci-libs/suitesparse (gentoo)