Key | Value |
---|---|
FileName | ./usr/lib64/libcholmod.so |
FileSize | 20 |
MD5 | 6F2E253DA80CF79FDEDFC042543C7032 |
RDS:package_id | 263811 |
SHA-1 | 1C4B6DE3CB83D37FB2B0C49DC3892FD6CA8AA639 |
SHA-256 | D5B10C6BE8B24DDA9E7CDF5521249399D1FDC86BE8F11B6BABEF4F851CD22135 |
SSDEEP | 3:EG80KLWhgXn:EGEIgX |
TLSH | |
insert-timestamp | 1654960642.9301739 |
source | modern.db |
hashlookup:parent-total | 12 |
hashlookup:trust | 100 |
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 |
---|---|
MD5 | B22FAD4726853779AE1F723BEDF839AF |
PackageArch | s390x |
PackageDescription | suitesparse 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | suitesparse-devel |
PackageRelease | 7.9 |
PackageVersion | 5.2.0 |
SHA-1 | 3E263A87CC45C3E3A6669E7FAA08FC9CDE1DD732 |
SHA-256 | 86EFE772EAD05EF98460FD2449CD44EF6C524B4CBAB42B70C8F531AA3CD06878 |
Key | Value |
---|---|
MD5 | 41DE5D20CD5402D1900DAE9369C215A7 |
PackageArch | s390x |
PackageDescription | suitesparse 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | suitesparse-devel |
PackageRelease | 150100.9.2.3 |
PackageVersion | 5.2.0 |
SHA-1 | 70D5C202D401AFE332C9524231885DF70257D7A5 |
SHA-256 | 89DBD56F2FC0E2E479A115249E2619B3B9341D241277536689B8E35C9581CC62 |
Key | Value |
---|---|
MD5 | 83C2A32986289AAD0B1EDE639360BEBB |
PackageArch | x86_64 |
PackageDescription | suitesparse 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | suitesparse-devel |
PackageRelease | 7.9 |
PackageVersion | 5.2.0 |
SHA-1 | BC147BBA87BACB0245DA3A54E60F348D934AB96C |
SHA-256 | 07964FE456BFA0D071019AFB9F7CA60898D15CA927E64891E2918B9A3110332D |
Key | Value |
---|---|
MD5 | 487136EF099668A4B5147AE23FC95F80 |
PackageArch | x86_64 |
PackageDescription | CHOLMOD 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. |
PackageMaintainer | https://bugs.opensuse.org |
PackageName | libcholmod3 |
PackageRelease | lp152.5.10 |
PackageVersion | 3.0.12 |
SHA-1 | 533A27AC1F6E7E87C034802016015A63D6F65B4E |
SHA-256 | 517BA5EDF48C4FA6DAD857B54A51E7E93FC700781CD227D6BDF2EE24FE487374 |
Key | Value |
---|---|
FileName | libcholmod3-3.0.12-7.9.x86_64.rpm |
FileSize | 909584 |
MD5 | 7226C780651CB269C4EE42247CB9DEC7 |
PackageArch | x86_64 |
PackageDescription | CHOLMOD 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | libcholmod3 |
PackageRelease | 7.9 |
PackageVersion | 3.0.12 |
RDS:package_id | 263809 |
SHA-1 | DC1DBD83CFA32D731935C81EFDE9C70340374837 |
SHA-256 | 20F2A132FA195FDD38D0B0707B797ECB942A74013A134AC412B7EF7EE55DF4B2 |
insert-timestamp | 1654958819.2049685 |
source | modern.db |
Key | Value |
---|---|
MD5 | 7FE306C918EDF74A521E3895EEDCE0DB |
PackageArch | x86_64 |
PackageDescription | suitesparse 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | suitesparse-devel |
PackageRelease | 150100.9.2.3 |
PackageVersion | 5.2.0 |
SHA-1 | 33BA20E4D7A72FD0B174EE873D6CA5E72EDB7336 |
SHA-256 | 033C42FCCDCE0418E548EA9F4D205BF87CFE3C2B787B95E206863843D08FB4B5 |
Key | Value |
---|---|
MD5 | CA0F9E4CF5E915238FAA33A2AEF9E2B3 |
PackageArch | x86_64 |
PackageDescription | CHOLMOD 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | libcholmod3 |
PackageRelease | 150100.9.2.3 |
PackageVersion | 3.0.12 |
SHA-1 | 7D5E64A666B262765DCC6D37B4DCDAA68D67A042 |
SHA-256 | 9DD9DBD412900A1ADF3B3D59BE99A10B792684DAECE454A633378DBC4D574040 |
Key | Value |
---|---|
MD5 | 113B1BEF52783B0B7742194C4EB9BE9A |
PackageArch | x86_64 |
PackageDescription | suitesparse 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. |
PackageMaintainer | https://bugs.opensuse.org |
PackageName | suitesparse-devel |
PackageRelease | lp152.5.10 |
PackageVersion | 5.2.0 |
SHA-1 | F9BCA9694AA128558B768E14B2C792E43A721899 |
SHA-256 | 325FFF875F8C55DD673675A1859AB49DADC3B043F9A979ECA573504C617043C5 |
Key | Value |
---|---|
MD5 | 5107DE150A8233DFD7B2FD5C5AFB4BC1 |
PackageArch | s390x |
PackageDescription | CHOLMOD 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | libcholmod3 |
PackageRelease | 150100.9.2.3 |
PackageVersion | 3.0.12 |
SHA-1 | F24AF88B2F82CCB3CBE1B682018E344A97188B12 |
SHA-256 | C5029200453CE7226A9F7B76DCF8582DC303E0CB3337C067828EDAA0060C2D88 |
Key | Value |
---|---|
MD5 | 5DBE3458EC44E98CBCC9D06B27CB6AD7 |
PackageArch | x86_64 |
PackageDescription | suitesparse 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. |
PackageMaintainer | https://bugs.opensuse.org |
PackageName | suitesparse-devel |
PackageRelease | lp151.4.1 |
PackageVersion | 5.2.0 |
SHA-1 | 1DCF5C386A380469F28BE5CFE98AFB588336A1C4 |
SHA-256 | 861664EB78F613B6EB78FC134CC1EC0D66AD0DB34AB8185A869469AC1F0B6703 |
Key | Value |
---|---|
MD5 | 414B876170CCF1306BE45C58B64EC259 |
PackageArch | s390x |
PackageDescription | CHOLMOD 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | libcholmod3 |
PackageRelease | 7.9 |
PackageVersion | 3.0.12 |
SHA-1 | F66CC8C93EA5839E97DB10110DF515F169848F70 |
SHA-256 | 6345D36EDF800CA91D83E55B4E3D1B211038E1CCA3A0C5D81496F5CDE6E3F0BC |
Key | Value |
---|---|
CRC32 | E887E1E7 |
FileName | libcholmod3-3.0.12-lp151.4.1.x86_64.rpm |
FileSize | 912408 |
MD5 | 5E48A8BEB8430F2158BF9182B3218C83 |
OpSystemCode | 362 |
PackageArch | x86_64 |
PackageDescription | CHOLMOD 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. |
PackageMaintainer | https://bugs.opensuse.org |
PackageName | libcholmod3 |
PackageRelease | lp151.4.1 |
PackageVersion | 3.0.12 |
ProductCode | 215189 |
SHA-1 | D675008C7F5ED5FDA3AFFDDC6E7E88C8DFD2318E |
SHA-256 | BF16D481CB3B0EEB863F93E25B4CAA11E7BDE5C3E647D57F0FA44DF90E1A63FA |
SpecialCode | |
db | nsrl_modern_rds |
insert-timestamp | 1647055540.9242947 |
source | NSRL |