Result for 1C4B6DE3CB83D37FB2B0C49DC3892FD6CA8AA639

Query result

Key Value
FileName./usr/lib64/libcholmod.so
FileSize20
MD56F2E253DA80CF79FDEDFC042543C7032
RDS:package_id263811
SHA-11C4B6DE3CB83D37FB2B0C49DC3892FD6CA8AA639
SHA-256D5B10C6BE8B24DDA9E7CDF5521249399D1FDC86BE8F11B6BABEF4F851CD22135
SSDEEP3:EG80KLWhgXn:EGEIgX
TLSH
insert-timestamp1654960642.9301739
sourcemodern.db
hashlookup:parent-total12
hashlookup:trust100

Network graph view

Parents (Total: 12)

The searched file hash is included in 12 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5B22FAD4726853779AE1F723BEDF839AF
PackageArchs390x
PackageDescriptionsuitesparse is a collection of libraries for computations involving sparse matrices. The suitesparse-devel package contains files needed for developing applications which use the suitesparse libraries.
PackageMaintainerhttps://www.suse.com/
PackageNamesuitesparse-devel
PackageRelease7.9
PackageVersion5.2.0
SHA-13E263A87CC45C3E3A6669E7FAA08FC9CDE1DD732
SHA-25686EFE772EAD05EF98460FD2449CD44EF6C524B4CBAB42B70C8F531AA3CD06878
Key Value
MD541DE5D20CD5402D1900DAE9369C215A7
PackageArchs390x
PackageDescriptionsuitesparse is a collection of libraries for computations involving sparse matrices. The suitesparse-devel package contains files needed for developing applications which use the suitesparse libraries.
PackageMaintainerhttps://www.suse.com/
PackageNamesuitesparse-devel
PackageRelease150100.9.2.3
PackageVersion5.2.0
SHA-170D5C202D401AFE332C9524231885DF70257D7A5
SHA-25689DBD56F2FC0E2E479A115249E2619B3B9341D241277536689B8E35C9581CC62
Key Value
MD583C2A32986289AAD0B1EDE639360BEBB
PackageArchx86_64
PackageDescriptionsuitesparse is a collection of libraries for computations involving sparse matrices. The suitesparse-devel package contains files needed for developing applications which use the suitesparse libraries.
PackageMaintainerhttps://www.suse.com/
PackageNamesuitesparse-devel
PackageRelease7.9
PackageVersion5.2.0
SHA-1BC147BBA87BACB0245DA3A54E60F348D934AB96C
SHA-25607964FE456BFA0D071019AFB9F7CA60898D15CA927E64891E2918B9A3110332D
Key Value
MD5487136EF099668A4B5147AE23FC95F80
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.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamelibcholmod3
PackageReleaselp152.5.10
PackageVersion3.0.12
SHA-1533A27AC1F6E7E87C034802016015A63D6F65B4E
SHA-256517BA5EDF48C4FA6DAD857B54A51E7E93FC700781CD227D6BDF2EE24FE487374
Key Value
FileNamelibcholmod3-3.0.12-7.9.x86_64.rpm
FileSize909584
MD57226C780651CB269C4EE42247CB9DEC7
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.
PackageMaintainerhttps://www.suse.com/
PackageNamelibcholmod3
PackageRelease7.9
PackageVersion3.0.12
RDS:package_id263809
SHA-1DC1DBD83CFA32D731935C81EFDE9C70340374837
SHA-25620F2A132FA195FDD38D0B0707B797ECB942A74013A134AC412B7EF7EE55DF4B2
insert-timestamp1654958819.2049685
sourcemodern.db
Key Value
MD57FE306C918EDF74A521E3895EEDCE0DB
PackageArchx86_64
PackageDescriptionsuitesparse is a collection of libraries for computations involving sparse matrices. The suitesparse-devel package contains files needed for developing applications which use the suitesparse libraries.
PackageMaintainerhttps://www.suse.com/
PackageNamesuitesparse-devel
PackageRelease150100.9.2.3
PackageVersion5.2.0
SHA-133BA20E4D7A72FD0B174EE873D6CA5E72EDB7336
SHA-256033C42FCCDCE0418E548EA9F4D205BF87CFE3C2B787B95E206863843D08FB4B5
Key Value
MD5CA0F9E4CF5E915238FAA33A2AEF9E2B3
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.
PackageMaintainerhttps://www.suse.com/
PackageNamelibcholmod3
PackageRelease150100.9.2.3
PackageVersion3.0.12
SHA-17D5E64A666B262765DCC6D37B4DCDAA68D67A042
SHA-2569DD9DBD412900A1ADF3B3D59BE99A10B792684DAECE454A633378DBC4D574040
Key Value
MD5113B1BEF52783B0B7742194C4EB9BE9A
PackageArchx86_64
PackageDescriptionsuitesparse is a collection of libraries for computations involving sparse matrices. The suitesparse-devel package contains files needed for developing applications which use the suitesparse libraries.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamesuitesparse-devel
PackageReleaselp152.5.10
PackageVersion5.2.0
SHA-1F9BCA9694AA128558B768E14B2C792E43A721899
SHA-256325FFF875F8C55DD673675A1859AB49DADC3B043F9A979ECA573504C617043C5
Key Value
MD55107DE150A8233DFD7B2FD5C5AFB4BC1
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.
PackageMaintainerhttps://www.suse.com/
PackageNamelibcholmod3
PackageRelease150100.9.2.3
PackageVersion3.0.12
SHA-1F24AF88B2F82CCB3CBE1B682018E344A97188B12
SHA-256C5029200453CE7226A9F7B76DCF8582DC303E0CB3337C067828EDAA0060C2D88
Key Value
MD55DBE3458EC44E98CBCC9D06B27CB6AD7
PackageArchx86_64
PackageDescriptionsuitesparse is a collection of libraries for computations involving sparse matrices. The suitesparse-devel package contains files needed for developing applications which use the suitesparse libraries.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamesuitesparse-devel
PackageReleaselp151.4.1
PackageVersion5.2.0
SHA-11DCF5C386A380469F28BE5CFE98AFB588336A1C4
SHA-256861664EB78F613B6EB78FC134CC1EC0D66AD0DB34AB8185A869469AC1F0B6703
Key Value
MD5414B876170CCF1306BE45C58B64EC259
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.
PackageMaintainerhttps://www.suse.com/
PackageNamelibcholmod3
PackageRelease7.9
PackageVersion3.0.12
SHA-1F66CC8C93EA5839E97DB10110DF515F169848F70
SHA-2566345D36EDF800CA91D83E55B4E3D1B211038E1CCA3A0C5D81496F5CDE6E3F0BC
Key Value
CRC32E887E1E7
FileNamelibcholmod3-3.0.12-lp151.4.1.x86_64.rpm
FileSize912408
MD55E48A8BEB8430F2158BF9182B3218C83
OpSystemCode362
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.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamelibcholmod3
PackageReleaselp151.4.1
PackageVersion3.0.12
ProductCode215189
SHA-1D675008C7F5ED5FDA3AFFDDC6E7E88C8DFD2318E
SHA-256BF16D481CB3B0EEB863F93E25B4CAA11E7BDE5C3E647D57F0FA44DF90E1A63FA
SpecialCode
dbnsrl_modern_rds
insert-timestamp1647055540.9242947
sourceNSRL