How to Install and Uninstall arbor-openmpi.x86_64 Package on Fedora 36
Last updated: November 27,2024
1. Install "arbor-openmpi.x86_64" package
Please follow the instructions below to install arbor-openmpi.x86_64 on Fedora 36
$
sudo dnf update
Copied
$
sudo dnf install
arbor-openmpi.x86_64
Copied
2. Uninstall "arbor-openmpi.x86_64" package
Please follow the step by step instructions below to uninstall arbor-openmpi.x86_64 on Fedora 36:
$
sudo dnf remove
arbor-openmpi.x86_64
Copied
$
sudo dnf autoremove
Copied
3. Information about the arbor-openmpi.x86_64 package on Fedora 36
Last metadata expiration check: 0:39:52 ago on Thu Sep 8 14:04:51 2022.
Available Packages
Name : arbor-openmpi
Version : 0.5.2
Release : 4.fc36
Architecture : x86_64
Size : 23 M
Source : arbor-0.5.2-4.fc36.src.rpm
Repository : fedora
Summary : OpenMPI build for arbor
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-openmpi
Version : 0.5.2
Release : 4.fc36
Architecture : x86_64
Size : 23 M
Source : arbor-0.5.2-4.fc36.src.rpm
Repository : fedora
Summary : OpenMPI build for arbor
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/