How to Install and Uninstall DSDP.i686 Package on Fedora 34

Last updated: October 05,2024

1. Install "DSDP.i686" package

This guide covers the steps necessary to install DSDP.i686 on Fedora 34


    
        
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                sudo dnf update
            
                    
    
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            $
        

        
            
                sudo dnf install
            
                        
                DSDP.i686
            
                    
    
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2. Uninstall "DSDP.i686" package

In this section, we are going to explain the necessary steps to uninstall DSDP.i686 on Fedora 34:


    
        
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                sudo dnf remove
            
                        
                DSDP.i686
            
                    
    
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            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the DSDP.i686 package on Fedora 34

Last metadata expiration check: 2:58:32 ago on Tue Sep 6 08:10:37 2022.
Available Packages
Name : DSDP
Version : 5.8
Release : 27.fc34
Architecture : i686
Size : 650 k
Source : DSDP-5.8-27.fc34.src.rpm
Repository : fedora
Summary : Software for semidefinite programming
URL : https://www.mcs.anl.gov/hs/software/DSDP/
License : DSDP
Description : DSDP 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. The software can be used as a set of subroutines, through Matlab,
: or by reading and writing to data files. 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.