Parents (Total: 6)

The searched file hash is included in 6 parent files which include package known and seen by metalookup. A sample is included below:

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	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	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	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