Result for 4DFD8A7701E37F1B8D109FAC1B528E001E7083C4

Query result

Key Value
FileName./usr/lib64/libcsparse.so.3.2.0
FileSize51704
MD54892282F2D13E29D7A654E18CE71E1A4
SHA-14DFD8A7701E37F1B8D109FAC1B528E001E7083C4
SHA-256D7D438EC0E4BBF2BD3ED5DA3A84C22DA80F0332ACD528BD4649760EE6ABCF410
SSDEEP768:cwbZne8QrCm25Q9L4zFe5oyfPco7LIbPykc95cMXX5SZo2gErr1s6G8+aw:7ByTtEAcb29WM5Fgrr1s6G8+a
TLSHT102336C4BF0A318FDC5EBC13483A7A626B9707475570A3A7B3184EB351A5BF24172EB12
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD54BC5D48359632FAFECDF9B9F3BA18ED2
PackageArchx86_64
PackageDescriptionCSparse is a small yet feature-rich sparse matrix package written specifically for a book. The purpose of the package is to demonstrate a wide range of sparse matrix algorithms in as concise a code as possible. CSparse is about 2,200 lines long (excluding its MATLAB interface, demo codes, and test codes), yet it contains algorithms (either asympotical optimal or fast in practice) for all of the following functions described below. A MATLAB interface is included. Note that the LU and Cholesky factorization algorithms are not as fast as UMFPACK or CHOLMOD. Other functions have comparable performance as their MATLAB equivalents (some are faster). Documentation is very terse in the code; it is fully documented in the book. Some indication of how to call the C functions in CSparse is given by the CSparse/MATLAB/*.m help files. CSparse is part of the SuiteSparse sparse matrix suite.
PackageNamelibcsparse3
PackageRelease59.1
PackageVersion3.2.0
SHA-100ABD18BC68E92199312293D256F4BF01E292473
SHA-2568115FC6C4C9569E53D2BA0950AD79ABFD92C89079923EB53FD2D53BB13116873