How to Install and Uninstall libadolc2-32bit Package on openSuSE Tumbleweed
Last updated: November 07,2024
1. Install "libadolc2-32bit" package
In this section, we are going to explain the necessary steps to install libadolc2-32bit on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
libadolc2-32bit
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2. Uninstall "libadolc2-32bit" package
Here is a brief guide to show you how to uninstall libadolc2-32bit on openSuSE Tumbleweed:
$
sudo zypper remove
libadolc2-32bit
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3. Information about the libadolc2-32bit package on openSuSE Tumbleweed
Information for package libadolc2-32bit:
----------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libadolc2-32bit
Version : 2.7.2-2.4
Arch : x86_64
Vendor : openSUSE
Installed Size : 897.5 KiB
Installed : No
Status : not installed
Source package : adolc-2.7.2-2.4.src
Upstream URL : https://github.com/coin-or/ADOL-C
Summary : Algorithmic Differentiation Library for C/C++
Description :
ADOL-C (Automatic Differentiation by OverLoading in C++) facilitates
the evaluation of first and higher derivatives of vector functions
written in C or C++. The resulting derivative evaluation routines may
be called from C/C++, Fortran, or any other language that can be
linked with C.
The numerical values of derivative vectors are obtained free of
truncation errors at a small multiple of the run time and randomly
accessed memory of the given function evaluation program.
----------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libadolc2-32bit
Version : 2.7.2-2.4
Arch : x86_64
Vendor : openSUSE
Installed Size : 897.5 KiB
Installed : No
Status : not installed
Source package : adolc-2.7.2-2.4.src
Upstream URL : https://github.com/coin-or/ADOL-C
Summary : Algorithmic Differentiation Library for C/C++
Description :
ADOL-C (Automatic Differentiation by OverLoading in C++) facilitates
the evaluation of first and higher derivatives of vector functions
written in C or C++. The resulting derivative evaluation routines may
be called from C/C++, Fortran, or any other language that can be
linked with C.
The numerical values of derivative vectors are obtained free of
truncation errors at a small multiple of the run time and randomly
accessed memory of the given function evaluation program.