Parents (Total: 77)

The searched file hash is included in 77 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	4BC5D48359632FAFECDF9B9F3BA18ED2
PackageArch	x86_64
PackageDescription	CSparse is a small yet feature-rich sparse matrix package written specifically for a book. The purpose of the package is to demonstrate a wide range of sparse matrix algorithms in as concise a code as possible. CSparse is about 2,200 lines long (excluding its MATLAB interface, demo codes, and test codes), yet it contains algorithms (either asympotical optimal or fast in practice) for all of the following functions described below. A MATLAB interface is included. Note that the LU and Cholesky factorization algorithms are not as fast as UMFPACK or CHOLMOD. Other functions have comparable performance as their MATLAB equivalents (some are faster). Documentation is very terse in the code; it is fully documented in the book. Some indication of how to call the C functions in CSparse is given by the CSparse/MATLAB/*.m help files. CSparse is part of the SuiteSparse sparse matrix suite.
PackageName	libcsparse3
PackageRelease	59.1
PackageVersion	3.2.0
SHA-1	00ABD18BC68E92199312293D256F4BF01E292473
SHA-256	8115FC6C4C9569E53D2BA0950AD79ABFD92C89079923EB53FD2D53BB13116873

Key	Value
MD5	91F9680E3555F8CE688ADED2B9E71A15
PackageArch	ppc64le
PackageDescription	suitesparse is a collection of libraries for computations involving sparse matrices. The package includes the following libraries: AMD approximate minimum degree ordering BTF permutation to block triangular form (beta) CAMD constrained approximate minimum degree ordering COLAMD column approximate minimum degree ordering CCOLAMD constrained column approximate minimum degree ordering CHOLMOD sparse Cholesky factorization CSparse a concise sparse matrix package CXSparse CSparse extended: complex matrix, int and long int support KLU sparse LU factorization, primarily for circuit simulation LDL a simple LDL factorization SQPR a multithread, multifrontal, rank-revealing sparse QR factorization method UMFPACK sparse LU factorization SuiteSparse_config configuration file for all the above packages. RBio read/write files in Rutherford/Boeing format
PackageMaintainer	Fedora Project
PackageName	suitesparse
PackageRelease	5.fc21
PackageVersion	4.2.1
SHA-1	04AE608C17795BF438EF858EB5E58EF9A7180188
SHA-256	2CA38DF19B2992DD2BC6EF30765A11E93F00AF51BB059EA34B68BBFF1B4E0B17

Key	Value
MD5	2C43326C617C2ACE56455E20EB5F5509
PackageArch	x86_64
PackageDescription	suitesparse is a collection of libraries for computations involving sparse matrices. The package includes the following libraries: AMD approximate minimum degree ordering BTF permutation to block triangular form (beta) CAMD constrained approximate minimum degree ordering COLAMD column approximate minimum degree ordering CCOLAMD constrained column approximate minimum degree ordering CHOLMOD sparse Cholesky factorization CSparse a concise sparse matrix package CXSparse CSparse extended: complex matrix, int and long int support KLU sparse LU factorization, primarily for circuit simulation LDL a simple LDL factorization SQPR a multithread, multifrontal, rank-revealing sparse QR factorization method UMFPACK sparse LU factorization SuiteSparse_config configuration file for all the above packages. RBio read/write files in Rutherford/Boeing format
PackageMaintainer	Fedora Project
PackageName	suitesparse
PackageRelease	5.fc33
PackageVersion	5.4.0
SHA-1	06D371D6EBB8E577DD4BF23D49DE048B3807B1F7
SHA-256	EA3F7D8D0D6264775E29DF28CB2474D0B5F9F1549251740B6462744D15473AC0

Key	Value
MD5	D2F1D74A535177BD72F8F1B765C0CCD7
PackageArch	x86_64
PackageDescription	CSparse is a small yet feature-rich sparse matrix package written specifically for a book. The purpose of the package is to demonstrate a wide range of sparse matrix algorithms in as concise a code as possible. CSparse is about 2,200 lines long (excluding its MATLAB interface, demo codes, and test codes), yet it contains algorithms (either asympotical optimal or fast in practice) for all of the following functions described below. A MATLAB interface is included. Note that the LU and Cholesky factorization algorithms are not as fast as UMFPACK or CHOLMOD. Other functions have comparable performance as their MATLAB equivalents (some are faster). Documentation is very terse in the code; it is fully documented in the book. Some indication of how to call the C functions in CSparse is given by the CSparse/MATLAB/*.m help files. CSparse is part of the SuiteSparse sparse matrix suite.
PackageName	libcsparse3
PackageRelease	85.70
PackageVersion	3.2.0
SHA-1	07CAC346EB474090F0BD84DDA1A3BDFDA1772FDB
SHA-256	6F78A2398D4577FA8A5558EA311B0B9B5E1D73ABFA4773FC73E8A623FCE49A02

Key	Value
MD5	A6A1E2CF78EE772FE15261A48356D815
PackageArch	s390
PackageDescription	suitesparse is a collection of libraries for computations involving sparse matrices. The package includes the following libraries: AMD approximate minimum degree ordering BTF permutation to block triangular form (beta) CAMD constrained approximate minimum degree ordering COLAMD column approximate minimum degree ordering CCOLAMD constrained column approximate minimum degree ordering CHOLMOD sparse Cholesky factorization CSparse a concise sparse matrix package CXSparse CSparse extended: complex matrix, int and long int support KLU sparse LU factorization, primarily for circuit simulation LDL a simple LDL factorization SQPR a multithread, multifrontal, rank-revealing sparse QR factorization method UMFPACK sparse LU factorization SuiteSparse_config configuration file for all the above packages. RBio read/write files in Rutherford/Boeing format
PackageMaintainer	Fedora Project
PackageName	suitesparse
PackageRelease	4.fc22
PackageVersion	4.3.1
SHA-1	09EBAF864850BEB45E14A045CC8AEE7390DD9B6F
SHA-256	DC3A6019791382F1774D7D033E4DA24AA2CDE7D866FDA1050A9D706AD107A062

Key	Value
MD5	DEA6BA35AB03D3DA921C1A6847E72862
PackageArch	aarch64
PackageDescription	suitesparse is a collection of libraries for computations involving sparse matrices. The package includes the following libraries: AMD approximate minimum degree ordering BTF permutation to block triangular form (beta) CAMD constrained approximate minimum degree ordering COLAMD column approximate minimum degree ordering CCOLAMD constrained column approximate minimum degree ordering CHOLMOD sparse Cholesky factorization CSparse a concise sparse matrix package CXSparse CSparse extended: complex matrix, int and long int support KLU sparse LU factorization, primarily for circuit simulation LDL a simple LDL factorization SQPR a multithread, multifrontal, rank-revealing sparse QR factorization method UMFPACK sparse LU factorization SuiteSparse_config configuration file for all the above packages. RBio read/write files in Rutherford/Boeing format
PackageMaintainer	Fedora Project
PackageName	suitesparse
PackageRelease	5.fc33
PackageVersion	5.4.0
SHA-1	0A8E05A260AF4977FCA7890A0B89A710E8427180
SHA-256	A2BC8D58F7E8D56EFCFC3D10F126B5FDAA2E0FB167FE23D96A88F6A896C4B2C0

Key	Value
MD5	F58F877D79510DC021B5A344C7330AFE
PackageArch	x86_64
PackageDescription	CSparse is a small yet feature-rich sparse matrix package written specifically for a book. The purpose of the package is to demonstrate a wide range of sparse matrix algorithms in as concise a code as possible. CSparse is about 2,200 lines long (excluding its MATLAB interface, demo codes, and test codes), yet it contains algorithms (either asympotical optimal or fast in practice) for all of the following functions described below. A MATLAB interface is included. Note that the LU and Cholesky factorization algorithms are not as fast as UMFPACK or CHOLMOD. Other functions have comparable performance as their MATLAB equivalents (some are faster). Documentation is very terse in the code; it is fully documented in the book. Some indication of how to call the C functions in CSparse is given by the CSparse/MATLAB/*.m help files. CSparse is part of the SuiteSparse sparse matrix suite.
PackageMaintainer	https://bugs.opensuse.org
PackageName	libcsparse3
PackageRelease	lp152.5.10
PackageVersion	3.2.0
SHA-1	0BE051E5FC2FA324DA7CB9C2F07194FFAE467A6F
SHA-256	D3E79D49CFB1EB5BD24B2DE96A0561EE2B5BA34D46C1268E2DE38CC6E37EB204

Key	Value
MD5	6C00F43A39E89C41BE48C4816CAD1D2E
PackageArch	ppc64le
PackageDescription	suitesparse is a collection of libraries for computations involving sparse matrices. The package includes the following libraries: AMD approximate minimum degree ordering BTF permutation to block triangular form (beta) CAMD constrained approximate minimum degree ordering COLAMD column approximate minimum degree ordering CCOLAMD constrained column approximate minimum degree ordering CHOLMOD sparse Cholesky factorization CSparse a concise sparse matrix package CXSparse CSparse extended: complex matrix, int and long int support KLU sparse LU factorization, primarily for circuit simulation LDL a simple LDL factorization SQPR a multithread, multifrontal, rank-revealing sparse QR factorization method UMFPACK sparse LU factorization SuiteSparse_config configuration file for all the above packages. RBio read/write files in Rutherford/Boeing format
PackageMaintainer	Fedora Project
PackageName	suitesparse
PackageRelease	2.fc23
PackageVersion	4.4.5
SHA-1	0E9B5815F1160B4B72314992E3ECD889DC406523
SHA-256	8E3E37358B93A2818C07D1139A208DBB82485BB8F971E2CAE5EE9F18C1F2A7EE

Key	Value
MD5	14E83CECAADA5D85B02174822FB1CAA1
PackageArch	i686
PackageDescription	suitesparse is a collection of libraries for computations involving sparse matrices. The package includes the following libraries: AMD approximate minimum degree ordering BTF permutation to block triangular form (beta) CAMD constrained approximate minimum degree ordering COLAMD column approximate minimum degree ordering CCOLAMD constrained column approximate minimum degree ordering CHOLMOD sparse Cholesky factorization CSparse a concise sparse matrix package CXSparse CSparse extended: complex matrix, int and long int support KLU sparse LU factorization, primarily for circuit simulation LDL a simple LDL factorization SQPR a multithread, multifrontal, rank-revealing sparse QR factorization method UMFPACK sparse LU factorization SuiteSparse_config configuration file for all the above packages. RBio read/write files in Rutherford/Boeing format
PackageMaintainer	Fedora Project
PackageName	suitesparse
PackageRelease	6.fc34
PackageVersion	5.4.0
SHA-1	0EED438F5CEE0BD7061DD38ABEF57E7BD3A39438
SHA-256	8FEF5182E19843B5989DC01637CC4839678C8B7FF67E7A05F353AA4E21B54689

Key	Value
MD5	291C84914D12D33F11B3ACE6A05EDB0C
PackageArch	i586
PackageDescription	CSparse is a small yet feature-rich sparse matrix package written specifically for a book. The purpose of the package is to demonstrate a wide range of sparse matrix algorithms in as concise a code as possible. CSparse is about 2,200 lines long (excluding its MATLAB interface, demo codes, and test codes), yet it contains algorithms (either asympotical optimal or fast in practice) for all of the following functions described below. A MATLAB interface is included. Note that the LU and Cholesky factorization algorithms are not as fast as UMFPACK or CHOLMOD. Other functions have comparable performance as their MATLAB equivalents (some are faster). Documentation is very terse in the code; it is fully documented in the book. Some indication of how to call the C functions in CSparse is given by the CSparse/MATLAB/*.m help files. CSparse is part of the SuiteSparse sparse matrix suite.
PackageMaintainer	https://bugs.opensuse.org
PackageName	libcsparse3
PackageRelease	43.6
PackageVersion	3.2.0
SHA-1	11B4EFD582EA5410DAEA4A9898FE518606CE4EB8
SHA-256	1EB8856A68175DD31E1D3B7555A1E6601A71DCE4A1A6B536FAF9D2A63DD48799