How to Install and Uninstall mpich-ofi Package on openSuSE Tumbleweed
Last updated: November 05,2024
1. Install "mpich-ofi" package
Please follow the steps below to install mpich-ofi on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
mpich-ofi
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2. Uninstall "mpich-ofi" package
Learn how to uninstall mpich-ofi on openSuSE Tumbleweed:
$
sudo zypper remove
mpich-ofi
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3. Information about the mpich-ofi package on openSuSE Tumbleweed
Information for package mpich-ofi:
----------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : mpich-ofi
Version : 4.1.2-1.4
Arch : x86_64
Vendor : openSUSE
Installed Size : 45.5 MiB
Installed : No
Status : not installed
Source package : mpich-ofi-4.1.2-1.4.src
Upstream URL : http://www.mpich.org/
Summary : High-performance and widely portable implementation of MPI
Description :
MPICH is a high performance and widely portable implementation of the Message
Passing Interface (MPI) standard.
The goals of MPICH are:
* to provide an MPI implementation that efficiently supports different
computation and communication platforms including commodity clusters
(desktop systems, shared-memory systems, multicore architectures),
high-speed networks and proprietary high-end computing systems
(Blue Gene, Cray)
* to enable cutting-edge research in MPI through an easy-to-extend modular
framework for other derived implementations
----------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : mpich-ofi
Version : 4.1.2-1.4
Arch : x86_64
Vendor : openSUSE
Installed Size : 45.5 MiB
Installed : No
Status : not installed
Source package : mpich-ofi-4.1.2-1.4.src
Upstream URL : http://www.mpich.org/
Summary : High-performance and widely portable implementation of MPI
Description :
MPICH is a high performance and widely portable implementation of the Message
Passing Interface (MPI) standard.
The goals of MPICH are:
* to provide an MPI implementation that efficiently supports different
computation and communication platforms including commodity clusters
(desktop systems, shared-memory systems, multicore architectures),
high-speed networks and proprietary high-end computing systems
(Blue Gene, Cray)
* to enable cutting-edge research in MPI through an easy-to-extend modular
framework for other derived implementations