How to Install and Uninstall libblacs2-mvapich2 Package on openSuSE Tumbleweed
Last updated: December 24,2024
1. Install "libblacs2-mvapich2" package
This guide let you learn how to install libblacs2-mvapich2 on openSuSE Tumbleweed
$
sudo zypper refresh
Copied
$
sudo zypper install
libblacs2-mvapich2
Copied
2. Uninstall "libblacs2-mvapich2" package
Please follow the steps below to uninstall libblacs2-mvapich2 on openSuSE Tumbleweed:
$
sudo zypper remove
libblacs2-mvapich2
Copied
3. Information about the libblacs2-mvapich2 package on openSuSE Tumbleweed
Information for package libblacs2-mvapich2:
-------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libblacs2-mvapich2
Version : 2.1.0-10.2
Arch : x86_64
Vendor : openSUSE
Installed Size : 387.9 KiB
Installed : No
Status : not installed
Source package : scalapack-mvapich2-2.1.0-10.2.src
Upstream URL : http://www.netlib.org/scalapack/
Summary : Basic Linear Algebra Communication Subprograms
Description :
The BLACS (Basic Linear Algebra Communication Subprograms) project
provides a linear algebra oriented message passing interface for
a large range of distributed memory platforms.
The length of time required to implement efficient distributed memory
algorithms makes it impractical to rewrite programs for every new
parallel machine. The BLACS exist in order to make linear algebra
applications both easier to program and more portable.
-------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libblacs2-mvapich2
Version : 2.1.0-10.2
Arch : x86_64
Vendor : openSUSE
Installed Size : 387.9 KiB
Installed : No
Status : not installed
Source package : scalapack-mvapich2-2.1.0-10.2.src
Upstream URL : http://www.netlib.org/scalapack/
Summary : Basic Linear Algebra Communication Subprograms
Description :
The BLACS (Basic Linear Algebra Communication Subprograms) project
provides a linear algebra oriented message passing interface for
a large range of distributed memory platforms.
The length of time required to implement efficient distributed memory
algorithms makes it impractical to rewrite programs for every new
parallel machine. The BLACS exist in order to make linear algebra
applications both easier to program and more portable.