Result for 00B0A4C3155ADE83D504E91975E8EC6E1E6F4432

Query result

Key Value
FileName./usr/share/doc/libcombblas-docs/html/inherit_graph_174.dot
FileSize364
MD5E5478C73BB392B3306F2AD73D43ACF8D
SHA-100B0A4C3155ADE83D504E91975E8EC6E1E6F4432
SHA-256FCB568E4E199C4B8CB45D18AE12B6D2940922711261425BE264F1650CA3E49A9
SSDEEP6:5OuM3H4/LAFy9bx9jtG9b8rrz2mEute5ty+63iHijqeyyn:suM34/0CjaAPzqfI+63iHij9
TLSHT1E2E0D84AD0859E2FC42205887454AD977C288621428E6F5C72A27A4F60E99E26158F1E
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize3014160
MD5F2AF3CBBB70D81E313F1A627EECC5144
PackageDescriptionan extensible parallel graph library for graph analytics (docs) The Combinatorial BLAS (CombBLAS) is an extensible distributed-memory parallel graph library offering a small but powerful set of linear algebra primitives specifically targeting graph analytics. . - The Combinatorial BLAS development influences the Graph BLAS standardization process. - It achieves scalability via its two dimensional distribution and coarse-grained parallelism. - CombBLAS powers HipMCL, a highly-scalable parallel implementation of the Markov Cluster Algorithm (MCL). - Operations among sparse matrices and vectors use arbitrary user defined semirings. . This package provides full HTML documentation for the CombBLAS API.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamelibcombblas-docs
PackageSectionlibdevel
PackageVersion1.6.2-3
SHA-1E49F9864A82A3D512DDFB90677EF0ABD2E1F8BA0
SHA-25624CBEC3BC71612805223CFD49932975D76C4E823A3551488CDCB8E103A8EB564
Key Value
FileSize2241572
MD5B6501023903A2CA9EAC25B15D1F0E37A
PackageDescriptionan extensible parallel graph library for graph analytics (docs) The Combinatorial BLAS (CombBLAS) is an extensible distributed-memory parallel graph library offering a small but powerful set of linear algebra primitives specifically targeting graph analytics. . - The Combinatorial BLAS development influences the Graph BLAS standardization process. - It achieves scalability via its two dimensional distribution and coarse-grained parallelism. - CombBLAS powers HipMCL, a highly-scalable parallel implementation of the Markov Cluster Algorithm (MCL). - Operations among sparse matrices and vectors use arbitrary user defined semirings. . This package provides full HTML documentation for the CombBLAS API.
PackageMaintainerDebian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageNamelibcombblas-docs
PackageSectionlibdevel
PackageVersion1.6.2-3
SHA-1D32759E12D219F2DE987702F7D0BC97BEE502933
SHA-25621411533BC01D320F4125F1D99A3C5B22AC3FC87933A88A13B09D109A1A9B96D