Result for CC039F87FF576179DD73AD3E1189569F48E17012

Query result

Key Value
FileName./usr/share/doc/libsuitesparse-dev/CHOLMOD_README.txt
FileSize3171
MD5FACC21D5BF9BCBF3E57A8B3C7BD1CAA0
RDS:package_id293685
SHA-1CC039F87FF576179DD73AD3E1189569F48E17012
SHA-2568EDAF18D26559B5AD4C66584AC5DC7BE98BE91E63772F400B0FF00A154D35C11
SSDEEP96:HngSFq2i1RC3meNvPlZtkJazjR8pZRCu90kACont8q1S:AWFSRC3bvPlZtkJazjRGeU0kACon5S
TLSHT10851634EBF8802759263C4D2D11D1D55EB30AAE2A8375C4D6858413C3BA2C7B477F766
insert-timestamp1678969810.5338743
sourceRDS.db
tar:gnameroot
tar:unameroot
hashlookup:parent-total134
hashlookup:trust100

Network graph view

Parents (Total: 134)

The searched file hash is included in 134 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5BE0DDB6AD01F035DD4BB174B2C0D002C
PackageArchs390x
PackageDescriptionCHOLMOD is a set of ANSI C routines for sparse Cholesky factorization and update/downdate. A MATLAB interface is provided. The performance of CHOLMOD was compared with 10 other codes in a paper by Nick Gould, Yifan Hu, and Jennifer Scott. see also their raw data. Comparing BCSLIB-EXT, CHOLMOD, MA57, MUMPS, Oblio, PARDISO, SPOOLES, SPRSBLKLLT, TAUCS, UMFPACK, and WSMP, on 87 large symmetric positive definite matrices, they found CHOLMOD to be fastest for 42 of the 87 matrices. Its run time is either fastest or within 10% of the fastest for 73 out of 87 matrices. Considering just the larger matrices, it is either the fastest or within 10% of the fastest for 40 out of 42 matrices. It uses the least amount of memory (or within 10% of the least) for 35 of the 42 larger matrices. Jennifer Scott and Yifan Hu also discuss the design considerations for a sparse direct code. CHOLMOD is part of the SuiteSparse sparse matrix suite.
PackageNamelibcholmod3
PackageRelease45.1
PackageVersion3.0.14
SHA-107F3F1BC6BFC7D0450E48C70DFB57B0B89B1BFFF
SHA-256142726F632A4DF5B8E12E4E22DCCFF35754EF869FB5AB16C46957FBBA65C5A49
Key Value
MD5A06B901C3AF9A7B9573BC0FA4F13FF4D
PackageArchi586
PackageDescriptionThis packages provides R-Matrix, one of the recommended packages.
PackageNameR-Matrix
PackageRelease160.46
PackageVersion1.3.4
SHA-1081288AFD62C550D858B250F4895E7B9930FC079
SHA-256DC8BC89A620D131C179ED3BE28DA265B14D49ED7C805DBAEF93806E139B3B35B
Key Value
MD5755E16B96250F75984C4C02FD12B1E8C
PackageArchx86_64
PackageDescriptionCHOLMOD is a set of ANSI C routines for sparse Cholesky factorization and update/downdate. A MATLAB interface is provided. The performance of CHOLMOD was compared with 10 other codes in a paper by Nick Gould, Yifan Hu, and Jennifer Scott. see also their raw data. Comparing BCSLIB-EXT, CHOLMOD, MA57, MUMPS, Oblio, PARDISO, SPOOLES, SPRSBLKLLT, TAUCS, UMFPACK, and WSMP, on 87 large symmetric positive definite matrices, they found CHOLMOD to be fastest for 42 of the 87 matrices. Its run time is either fastest or within 10% of the fastest for 73 out of 87 matrices. Considering just the larger matrices, it is either the fastest or within 10% of the fastest for 40 out of 42 matrices. It uses the least amount of memory (or within 10% of the least) for 35 of the 42 larger matrices. Jennifer Scott and Yifan Hu also discuss the design considerations for a sparse direct code. CHOLMOD is part of the SuiteSparse sparse matrix suite.
PackageNamelibcholmod3
PackageRelease85.3
PackageVersion3.0.14
SHA-108C4CEE983936BAF27DC80BF2A38B4EC17D2CD2C
SHA-256A890C4B91821AF3DD3B509B3325AFB55DCE11920122F26EC8B07D7613182DC3B
Key Value
MD50B5472F718014AC4C5B8150047287B40
PackageArchs390x
PackageDescriptionA language and environment for statistical computing and graphics. R is similar to the award-winning S system, which was developed at Bell Laboratories by John Chambers et al. It provides a wide variety of statistical and graphical techniques (linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, ...). R is designed as a true computer language with control-flow constructions for iteration and alternation, and it allows users to add additional functionality by defining new functions. For computationally intensive tasks, C, C++ and Fortran code can be linked and called at run time.
PackageMaintainerFedora Project
PackageNameR-core
PackageRelease1.el8
PackageVersion4.1.1
SHA-108E03E073B8E8B10B9E85123DE9D76B5F9C29A78
SHA-256253FBBD3E1B70A54CA8956A9E89200B6AAAF2A1900B790294978B3733465CC18
Key Value
MD5A4E647D07CB53F8DD54326DE6741F34C
PackageArchx86_64
PackageDescriptionCHOLMOD is a set of ANSI C routines for sparse Cholesky factorization and update/downdate. A MATLAB interface is provided. The performance of CHOLMOD was compared with 10 other codes in a paper by Nick Gould, Yifan Hu, and Jennifer Scott. see also their raw data. Comparing BCSLIB-EXT, CHOLMOD, MA57, MUMPS, Oblio, PARDISO, SPOOLES, SPRSBLKLLT, TAUCS, UMFPACK, and WSMP, on 87 large symmetric positive definite matrices, they found CHOLMOD to be fastest for 42 of the 87 matrices. Its run time is either fastest or within 10% of the fastest for 73 out of 87 matrices. Considering just the larger matrices, it is either the fastest or within 10% of the fastest for 40 out of 42 matrices. It uses the least amount of memory (or within 10% of the least) for 35 of the 42 larger matrices. Jennifer Scott and Yifan Hu also discuss the design considerations for a sparse direct code. CHOLMOD is part of the SuiteSparse sparse matrix suite.
PackageNamelibcholmod3
PackageReleasebp151.44.1
PackageVersion3.0.14
SHA-1094E1602C2ED2D971F4DFFE045C8B8833794A520
SHA-256CDA294767969A938A52C489AE33EF1015770B3981422B65CC030408EBE3DD68E
Key Value
FileSize3622804
MD5CF62D9DF8677777F0BCA5A64B4EC2870
PackageDescriptionGNU R package of classes for dense and sparse matrices This CRAN package provides S4 classes and methods for numerical linear algebra using dense or sparse matrices. The sparse matrix implementation uses code from the LDL sparse matrix package and code from the Metis package of partitioning algorithms.
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-matrix
PackageSectiongnu-r
PackageVersion1.3-4-2
SHA-10E240917A0FDBA58E4A42C04441D3F10C715C9D9
SHA-25659C99303B11288186765FC0A9E78851A2E8057373DD538C5E61A29ED3002199E
Key Value
MD5929C899A1884F233F6CA878523729123
PackageArchx86_64
PackageDescriptionThis packages provides R-Matrix, one of the recommended packages.
PackageNameR-Matrix
PackageRelease45.1
PackageVersion1.3.4
SHA-1103A5E857E753287E5609231CA04D4FEAD6AD459
SHA-256C1D49AE365420A7C8590C60FEA54734A349F3DA1C4BC44886D86005D3267A202
Key Value
MD53CA9F8B52C81449C328759F6C890F6B7
PackageArcharmv7hl
PackageDescription`GNU S' - A language and environment for statistical computing and graphics. R is similar to the S system, which was developed at Bell Laboratories by John Chambers et al. It provides a wide variety of statistical and graphical techniques (linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, ...). R is designed as a true computer language with control-flow constructions for iteration and alternation, and it allows users to add additional functionality by defining new functions. For computationally intensive tasks, C, C++ and Fortran code can be linked and called at run time.
PackageMaintainerjoequant <joequant>
PackageNameR-base
PackageRelease3.mga9
PackageVersion4.1.3
SHA-111C37D237DE880893A491B1743C39B4F26AD0060
SHA-2567C4816B762595A25E43B183D45A6D760A35EF109039FC7063664902CD248185A
Key Value
FileSize3649004
MD58235D26193A63A1D72FEEB3CA61BFA14
PackageDescriptionGNU R package of classes for dense and sparse matrices This CRAN package provides S4 classes and methods for numerical linear algebra using dense or sparse matrices. The sparse matrix implementation uses code from the LDL sparse matrix package and code from the Metis package of partitioning algorithms.
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-matrix
PackageSectiongnu-r
PackageVersion1.3-4-2
SHA-11203B929BB186FEB68571B39776580892AE27A21
SHA-256B7F928EA8F7BEBC439BA87130C52D0F919E67C1D9130B04B62168F3DF70FD9E6
Key Value
FileNamehttp://dl-cdn.alpinelinux.org/alpine/latest-stable//community//armv7//suitesparse-doc-5.10.1-r1.apk
MD5FFFE426AB66B96708625E43FBF1FAF6B
SHA-113000B39F5D66773AA4C8946A17C962DC0F6CCB4
SHA-2561F9D8C45D490F5E61190C78A60592B80160E39AADAA90B986D5EC481083B35DA
SSDEEP49152:CpcNn6detK4Y2HaIgnZsyOYZjfXJ0fJVI8ic56zeCQvdqWGoeCG3XCnebgD:GcNSeYP2x+pZrXci8iondLGpSneby
TLSHT150B53321A5C98A244C09BAF7DA13BF8E9438BE57100BAF76FB2D85D4C35F1B16421E47