How to Install and Uninstall scalasca-openmpi.x86_64 Package on Fedora 38

Last updated: November 16,2024

1. Install "scalasca-openmpi.x86_64" package

This is a short guide on how to install scalasca-openmpi.x86_64 on Fedora 38


    
        
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                sudo dnf update
            
                    
    
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            $
        

        
            
                sudo dnf install
            
                        
                scalasca-openmpi.x86_64
            
                    
    
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2. Uninstall "scalasca-openmpi.x86_64" package

Please follow the step by step instructions below to uninstall scalasca-openmpi.x86_64 on Fedora 38:


    
        
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                sudo dnf remove
            
                        
                scalasca-openmpi.x86_64
            
                    
    
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            $
        

        
            
                sudo dnf autoremove
            
                    
    
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3. Information about the scalasca-openmpi.x86_64 package on Fedora 38

Last metadata expiration check: 3:48:41 ago on Sat Mar 16 16:59:57 2024.
Available Packages
Name : scalasca-openmpi
Version : 2.6.1
Release : 2.fc38
Architecture : x86_64
Size : 1.0 M
Source : scalasca-2.6.1-2.fc38.src.rpm
Repository : fedora
Summary : Toolset for performance analysis of large-scale parallel applications - openmpi
URL : http://www.scalasca.org/
License : BSD-3-Clause AND GPL-3.0-or-later WITH Bison-exception-2.0
Description :
: Scalasca is a software tool that supports the performance optimization
: of parallel programs by measuring and analyzing their runtime
: behavior. The analysis identifies potential performance bottlenecks –
: in particular those concerning communication and synchronization – and
: offers guidance in exploring their causes.
:
: Scalasca targets mainly scientific and engineering applications based
: on the programming interfaces MPI and OpenMP, including hybrid
: applications based on a combination of the two. The tool has been
: specifically designed for use on large-scale systems, but is also well
: suited for small- and medium-scale HPC platforms.