How to Install and Uninstall arbor-devel.x86_64 Package on Fedora 39
Last updated: October 07,2024
1. Install "arbor-devel.x86_64" package
Learn how to install arbor-devel.x86_64 on Fedora 39
$
sudo dnf update
Copied
$
sudo dnf install
arbor-devel.x86_64
Copied
2. Uninstall "arbor-devel.x86_64" package
Here is a brief guide to show you how to uninstall arbor-devel.x86_64 on Fedora 39:
$
sudo dnf remove
arbor-devel.x86_64
Copied
$
sudo dnf autoremove
Copied
3. Information about the arbor-devel.x86_64 package on Fedora 39
Last metadata expiration check: 2:07:36 ago on Thu Mar 7 11:44:58 2024.
Available Packages
Name : arbor-devel
Version : 0.7
Release : 10.fc39
Architecture : x86_64
Size : 1.3 M
Source : arbor-0.7-10.fc39.src.rpm
Repository : updates
Summary : Development files for arbor
URL : https://github.com/arbor-sim/arbor
License : BSD-3-Clause
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-devel
Version : 0.7
Release : 10.fc39
Architecture : x86_64
Size : 1.3 M
Source : arbor-0.7-10.fc39.src.rpm
Repository : updates
Summary : Development files for arbor
URL : https://github.com/arbor-sim/arbor
License : BSD-3-Clause
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/