How to Install and Uninstall cube.x86_64 Package on Red Hat Enterprise Linux 8 (RHEL 8)
Last updated: November 29,2024
1. Install "cube.x86_64" package
This tutorial shows how to install cube.x86_64 on Red Hat Enterprise Linux 8 (RHEL 8)
$
sudo dnf update
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$
sudo dnf install
cube.x86_64
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2. Uninstall "cube.x86_64" package
Please follow the guidelines below to uninstall cube.x86_64 on Red Hat Enterprise Linux 8 (RHEL 8):
$
sudo dnf remove
cube.x86_64
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$
sudo dnf autoremove
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3. Information about the cube.x86_64 package on Red Hat Enterprise Linux 8 (RHEL 8)
Last metadata expiration check: 0:21:45 ago on Mon Feb 26 15:59:38 2024.
Available Packages
Name : cube
Version : 4.5
Release : 1.el8
Architecture : x86_64
Size : 1.3 M
Source : cube-4.5-1.el8.src.rpm
Repository : epel
Summary : CUBE Uniform Behavioral Encoding generic presentation component
URL : http://www.scalasca.org/software/cube-4.x/download.html
License : BSD
Description : CUBE (CUBE Uniform Behavioral Encoding) is a generic presentation component
: suitable for displaying a wide variety of performance metrics for parallel
: programs including MPI and OpenMP applications. CUBE allows interactive
: exploration of a multidimensional performance space in a scalable fashion.
: Scalability is achieved in two ways: hierarchical decomposition of individual
: dimensions and aggregation across different dimensions. All performance
: metrics are uniformly accommodated in the same display and thus provide the
: ability to easily compare the effects of different kinds of performance
: behavior.
Available Packages
Name : cube
Version : 4.5
Release : 1.el8
Architecture : x86_64
Size : 1.3 M
Source : cube-4.5-1.el8.src.rpm
Repository : epel
Summary : CUBE Uniform Behavioral Encoding generic presentation component
URL : http://www.scalasca.org/software/cube-4.x/download.html
License : BSD
Description : CUBE (CUBE Uniform Behavioral Encoding) is a generic presentation component
: suitable for displaying a wide variety of performance metrics for parallel
: programs including MPI and OpenMP applications. CUBE allows interactive
: exploration of a multidimensional performance space in a scalable fashion.
: Scalability is achieved in two ways: hierarchical decomposition of individual
: dimensions and aggregation across different dimensions. All performance
: metrics are uniformly accommodated in the same display and thus provide the
: ability to easily compare the effects of different kinds of performance
: behavior.