Result for 06E816D8ED805A1492A240A8AAED511F3CAF5B82

Query result

Key Value
FileName./usr/share/doc/dsdp-doc/html/sdpvec_8c-source.html
FileSize51732
MD5CD010DA454EE53FCB1CA451A0564D31D
SHA-106E816D8ED805A1492A240A8AAED511F3CAF5B82
SHA-256CE101AB496B3337FFF437C8E57B03DFF1056ABB52A38ADD261EC3B8AF6BED710
SSDEEP768:IUPjhszpyMjuSvu8roTvqtRWHn5Ii3cKsJbNJnRYLOX+R0rZ/:/PVs5uSvu8roTvqtsnINJnuLOX+R0rF
TLSHT198330461DCE75C376A7284F7888D3E35A8D52A3EC3562724A1DC9773439BED07803A4A
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
FileSize785328
MD53F500F92D9DD29738D5874821C0006A3
PackageDescriptionSoftware for Semidefinite Programming The DSDP software is a free open source implementation of an interior-point method for semidefinite programming. It provides primal and dual solutions, exploits low-rank structure and sparsity in the data, and has relatively low memory requirements for an interior-point method. It allows feasible and infeasible starting points and provides approximate certificates of infeasibility when no feasible solution exists. The dual-scaling algorithm implemented in this package has a convergence proof and worst-case polynomial complexity under mild assumptions on the data. Furthermore, the solver offers scalable parallel performance for large problems and a well documented interface. Some of the most popular applications of semidefinite programming and linear matrix inequalities (LMI) are model control, truss topology design, and semidefinite relaxations of combinatorial and global optimization problems. . This package contains the documentation and examples.
PackageMaintainerUbuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageNamedsdp-doc
PackageSectiondoc
PackageVersion5.8-5
SHA-10046399F3CA144336313A066FF029964D5CF2B80
SHA-256C22C0B0F9CBE888956A18E3E58A1B14C03D8212CCBBAA89A17DAF69B49529B31