Parents (Total: 17)

The searched file hash is included in 17 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	BE0DDB6AD01F035DD4BB174B2C0D002C
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.
PackageName	libcholmod3
PackageRelease	45.1
PackageVersion	3.0.14
SHA-1	07F3F1BC6BFC7D0450E48C70DFB57B0B89B1BFFF
SHA-256	142726F632A4DF5B8E12E4E22DCCFF35754EF869FB5AB16C46957FBBA65C5A49

Key	Value
MD5	755E16B96250F75984C4C02FD12B1E8C
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.
PackageName	libcholmod3
PackageRelease	85.3
PackageVersion	3.0.14
SHA-1	08C4CEE983936BAF27DC80BF2A38B4EC17D2CD2C
SHA-256	A890C4B91821AF3DD3B509B3325AFB55DCE11920122F26EC8B07D7613182DC3B

Key	Value
MD5	A4E647D07CB53F8DD54326DE6741F34C
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.
PackageName	libcholmod3
PackageRelease	bp151.44.1
PackageVersion	3.0.14
SHA-1	094E1602C2ED2D971F4DFFE045C8B8833794A520
SHA-256	CDA294767969A938A52C489AE33EF1015770B3981422B65CC030408EBE3DD68E

Key	Value
MD5	9370CBE8EB01C1036150A37FA56C84B1
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.
PackageName	libcholmod3
PackageRelease	bp153.44.4
PackageVersion	3.0.14
SHA-1	1633BB64B57529B30B6B8C9DF1C42D467D70BF5B
SHA-256	88CB6F19AB0E5AE5265F5F8F97B5AC2997F3E2FEC9B1833572C0B0E8C6ADEAB3

Key	Value
MD5	0EE7F85740BF35C237C50E8C439248E3
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.
PackageName	libcholmod3
PackageRelease	lp151.84.1
PackageVersion	3.0.14
SHA-1	202350ADB91E2977204CB81391FD94572582A6F8
SHA-256	824E832965B9D460100E82889958D24D9D1F74161FADEA873F8A0E417E53407F

Key	Value
MD5	5A1CF3E368C35B0CFCB82B2DFDC9D769
PackageArch	i586
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	43.6
PackageVersion	3.0.14
SHA-1	29EDCB6A1347B836F69615A5657B6B366E78B9E0
SHA-256	4832938A6386D1787C669ADB6D9DEFD6AED9050F53FBA774191B4AB25D1AE615

Key	Value
MD5	6386504BB6444FC219E45F2627F0D925
PackageArch	i586
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.
PackageName	libcholmod3
PackageRelease	45.3
PackageVersion	3.0.14
SHA-1	4ECDA9DC8056C818B9C005DAD42560F331ED4242
SHA-256	418F6C07F64523498F525E3939C5943897FF0046752C1663382970A59C63A071

Key	Value
MD5	2944CDDACEA549B00780E25D771B390C
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.
PackageName	libcholmod3
PackageRelease	85.70
PackageVersion	3.0.14
SHA-1	5626653D5C1A0A75359FA86E8CF2D7F58AECBD56
SHA-256	196D889F864D0E0D7CC71A9F310A054020EE3A202D12CF59B64C7C4A64E400FE

Key	Value
MD5	767D599CC12E0EEA9420648C7CB05A65
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.
PackageName	libcholmod3
PackageRelease	bp152.44.3
PackageVersion	3.0.14
SHA-1	7AB555F31BCDE8D5C02F8C9B51EBED38E2D9469C
SHA-256	1E7DCF4B2A2F2E743FD5D3EB1995ECC9E6FCDA0CB4F5E0B7DF114B3A08FB44C8

Key	Value
MD5	B031265A052427FF6E054DDAA83E1667
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.
PackageName	libcholmod3
PackageRelease	bp150.44.1
PackageVersion	3.0.14
SHA-1	8292EF2135F9C42DCE32E982061AA82FFC9F20C9
SHA-256	773510A02E8F190DFF99CE2F57E3ACFD32A4FD3BB9789920F5F43F73E652E1EF