How to Install and Uninstall arbor-mpich-devel.i686 Package on Fedora 35
Last updated: November 25,2024
1. Install "arbor-mpich-devel.i686" package
This is a short guide on how to install arbor-mpich-devel.i686 on Fedora 35
$
sudo dnf update
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$
sudo dnf install
arbor-mpich-devel.i686
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2. Uninstall "arbor-mpich-devel.i686" package
This is a short guide on how to uninstall arbor-mpich-devel.i686 on Fedora 35:
$
sudo dnf remove
arbor-mpich-devel.i686
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$
sudo dnf autoremove
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3. Information about the arbor-mpich-devel.i686 package on Fedora 35
Last metadata expiration check: 3:23:29 ago on Wed Sep 7 08:25:01 2022.
Available Packages
Name : arbor-mpich-devel
Version : 0.5.2
Release : 4.fc35
Architecture : i686
Size : 1.4 M
Source : arbor-0.5.2-4.fc35.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/
Available Packages
Name : arbor-mpich-devel
Version : 0.5.2
Release : 4.fc35
Architecture : i686
Size : 1.4 M
Source : arbor-0.5.2-4.fc35.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/