How to Install and Uninstall arpack.x86_64 Package on Red Hat Enterprise Linux 8 (RHEL 8)
Last updated: November 23,2024
1. Install "arpack.x86_64" package
This guide let you learn how to install arpack.x86_64 on Red Hat Enterprise Linux 8 (RHEL 8)
$
sudo dnf update
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$
sudo dnf install
arpack.x86_64
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2. Uninstall "arpack.x86_64" package
Please follow the steps below to uninstall arpack.x86_64 on Red Hat Enterprise Linux 8 (RHEL 8):
$
sudo dnf remove
arpack.x86_64
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$
sudo dnf autoremove
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3. Information about the arpack.x86_64 package on Red Hat Enterprise Linux 8 (RHEL 8)
Last metadata expiration check: 1:58:21 ago on Mon Feb 26 15:59:38 2024.
Available Packages
Name : arpack
Version : 3.7.0
Release : 1.el8
Architecture : x86_64
Size : 194 k
Source : arpack-3.7.0-1.el8.src.rpm
Repository : epel
Summary : Fortran 77 subroutines for solving large scale eigenvalue problems
URL : https://github.com/opencollab/arpack-ng
License : BSD
Description : ARPACK is a collection of Fortran 77 subroutines designed to solve large
: scale eigenvalue problems.
:
: The package is designed to compute a few eigenvalues and corresponding
: eigenvectors of a general n by n matrix A. It is most appropriate for
: large sparse or structured matrices A where structured means that a
: matrix-vector product w <- Av requires order n rather than the usual
: order n**2 floating point operations. This software is based upon an
: algorithmic variant of the Arnoldi process called the Implicitly
: Restarted Arnoldi Method (IRAM).
Available Packages
Name : arpack
Version : 3.7.0
Release : 1.el8
Architecture : x86_64
Size : 194 k
Source : arpack-3.7.0-1.el8.src.rpm
Repository : epel
Summary : Fortran 77 subroutines for solving large scale eigenvalue problems
URL : https://github.com/opencollab/arpack-ng
License : BSD
Description : ARPACK is a collection of Fortran 77 subroutines designed to solve large
: scale eigenvalue problems.
:
: The package is designed to compute a few eigenvalues and corresponding
: eigenvectors of a general n by n matrix A. It is most appropriate for
: large sparse or structured matrices A where structured means that a
: matrix-vector product w <- Av requires order n rather than the usual
: order n**2 floating point operations. This software is based upon an
: algorithmic variant of the Arnoldi process called the Implicitly
: Restarted Arnoldi Method (IRAM).