How to Install and Uninstall dsdp-doc Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: November 24,2024

1. Install "dsdp-doc" package

This is a short guide on how to install dsdp-doc on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                dsdp-doc
            
                    
    
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2. Uninstall "dsdp-doc" package

Please follow the guidance below to uninstall dsdp-doc on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                dsdp-doc
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the dsdp-doc package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: dsdp-doc
Priority: extra
Section: universe/doc
Installed-Size: 8004
Maintainer: Ubuntu Developers
Original-Maintainer: Soeren Sonnenburg
Architecture: all
Source: dsdp
Version: 5.8-9.1ubuntu2
Recommends: dsdp
Filename: pool/universe/d/dsdp/dsdp-doc_5.8-9.1ubuntu2_all.deb
Size: 530538
MD5sum: cd3e84f52cc253ba1cb7a79ca9dfaf34
SHA1: c8a72e3dc87c06309a3ad4163c3bd9259debf3da
SHA256: 8782a4dfa56d23c0ea03d8ebdde6f65d96636067699adf5e589e91adc25df8da
Description-en: Software 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.
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This package contains the documentation and examples.
Description-md5: 26082894d8d34e85cfb5511f23cc16cd
Homepage: http://www-unix.mcs.anl.gov/DSDP/
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu