How to Install and Uninstall arbor-mpich-devel.x86_64 Package on Fedora 36

Last updated: November 25,2024

1. Install "arbor-mpich-devel.x86_64" package

Please follow the step by step instructions below to install arbor-mpich-devel.x86_64 on Fedora 36


    
        
            $
        

        
            
                sudo dnf update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf install
            
                        
                arbor-mpich-devel.x86_64
            
                    
    
    Copied

2. Uninstall "arbor-mpich-devel.x86_64" package

In this section, we are going to explain the necessary steps to uninstall arbor-mpich-devel.x86_64 on Fedora 36:


    
        
            $
        

        
            
                sudo dnf remove
            
                        
                arbor-mpich-devel.x86_64
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the arbor-mpich-devel.x86_64 package on Fedora 36

Last metadata expiration check: 4:25:44 ago on Thu Sep 8 08:04:50 2022.
Available Packages
Name : arbor-mpich-devel
Version : 0.5.2
Release : 4.fc36
Architecture : x86_64
Size : 1.3 M
Source : arbor-0.5.2-4.fc36.src.rpm
Repository : fedora
Summary : Development files for arbor-mpich
URL : https://github.com/arbor-sim/arbor
License : BSD
Description : Arbor is a high-performance library for Computational Neuroscience simulations.
:
: Some key features include:
:
: - Asynchronous spike exchange that overlaps compute and communication.
: - Efficient sampling of voltage and current on all back ends.
: - Efficient implementation of all features on GPU.
: - Reporting of memory and energy consumption (when available on platform).
: - An API for addition of new cell types, e.g. LIF and Poisson spike generators.
: - Validation tests against numeric/analytic models and NEURON.
:
: Documentation is available at https://arbor.readthedocs.io/en/latest/