How to Install and Uninstall metis_5_1_0-gnu-hpc Package on openSUSE Leap
Last updated: December 24,2024
1. Install "metis_5_1_0-gnu-hpc" package
This guide let you learn how to install metis_5_1_0-gnu-hpc on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
metis_5_1_0-gnu-hpc
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2. Uninstall "metis_5_1_0-gnu-hpc" package
Please follow the steps below to uninstall metis_5_1_0-gnu-hpc on openSUSE Leap:
$
sudo zypper remove
metis_5_1_0-gnu-hpc
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3. Information about the metis_5_1_0-gnu-hpc package on openSUSE Leap
Information for package metis_5_1_0-gnu-hpc:
--------------------------------------------
Repository : Update repository with updates from SUSE Linux Enterprise 15
Name : metis_5_1_0-gnu-hpc
Version : 5.1.0-150100.9.5.2
Arch : x86_64
Vendor : SUSE LLC
Installed Size : 220.3 KiB
Installed : No
Status : not installed
Source package : metis_5_1_0-gnu-hpc-5.1.0-150100.9.5.2.src
Upstream URL : http://glaros.dtc.umn.edu/gkhome/metis/metis/overview
Summary : Serial Graph Partitioning and Fill-reducing Matrix Ordering
Description :
METIS is a family of programs for partitioning unstructured graphs and hypergraph
and computing fill-reducing orderings of sparse matrices. The underlying algorithms
used by METIS are based on a multilevel paradigm that, at the time, had been
shown to produce quality results and scale to large problems.
--------------------------------------------
Repository : Update repository with updates from SUSE Linux Enterprise 15
Name : metis_5_1_0-gnu-hpc
Version : 5.1.0-150100.9.5.2
Arch : x86_64
Vendor : SUSE LLC
Installed Size : 220.3 KiB
Installed : No
Status : not installed
Source package : metis_5_1_0-gnu-hpc-5.1.0-150100.9.5.2.src
Upstream URL : http://glaros.dtc.umn.edu/gkhome/metis/metis/overview
Summary : Serial Graph Partitioning and Fill-reducing Matrix Ordering
Description :
METIS is a family of programs for partitioning unstructured graphs and hypergraph
and computing fill-reducing orderings of sparse matrices. The underlying algorithms
used by METIS are based on a multilevel paradigm that, at the time, had been
shown to produce quality results and scale to large problems.