How to Install and Uninstall zfp.x86_64 Package on CentOS 8 / RHEL 8
Last updated: December 25,2024
1. Install "zfp.x86_64" package
Please follow the steps below to install zfp.x86_64 on CentOS 8 / RHEL 8
$
sudo dnf update
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$
sudo dnf install
zfp.x86_64
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2. Uninstall "zfp.x86_64" package
This guide covers the steps necessary to uninstall zfp.x86_64 on CentOS 8 / RHEL 8:
$
sudo dnf remove
zfp.x86_64
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$
sudo dnf autoremove
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3. Information about the zfp.x86_64 package on CentOS 8 / RHEL 8
Last metadata expiration check: 1 day, 9:08:46 ago on Sun May 9 13:03:46 2021.
Available Packages
Name : zfp
Version : 0.5.5
Release : 1.el8
Architecture : x86_64
Size : 65 k
Source : zfp-0.5.5-1.el8.src.rpm
Repository : epel
Summary : Library for compressed numerical arrays with high throughput R/W random access
URL : https://computation.llnl.gov/projects/floating-point-compression
License : BSD
Description : This is zfp, an open source C/C++ library for compressed numerical arrays
: that support high throughput read and write random access. zfp was written by
: Peter Lindstrom at Lawrence Livermore National Laboratory, and is loosely
: based on the algorithm described in the following paper:
:
: Peter Lindstrom
: "Fixed-Rate Compressed Floating-Point Arrays"
: IEEE Transactions on Visualization and Computer Graphics,
: 20(12):2674-2683, December 2014
: doi:10.1109/TVCG.2014.2346458
:
: zfp was originally designed for floating-point data only, but has been
: extended to also support integer data, and could for instance be used to
: compress images and quantized volumetric data. To achieve high compression
: ratios, zfp uses lossy but optionally error-bounded compression. Although
: bit-for-bit lossless compression of floating-point data is not always
: possible, zfp is usually accurate to within machine epsilon in near-lossless
: mode.
:
: zfp works best for 2D and 3D arrays that exhibit spatial coherence, such as
: smooth fields from physics simulations, images, regularly sampled terrain
: surfaces, etc. Although zfp also provides a 1D array class that can be used
: for 1D signals such as audio, or even unstructured floating-point streams,
: the compression scheme has not been well optimized for this use case, and
: rate and quality may not be competitive with floating-point compressors
: designed specifically for 1D streams.
Available Packages
Name : zfp
Version : 0.5.5
Release : 1.el8
Architecture : x86_64
Size : 65 k
Source : zfp-0.5.5-1.el8.src.rpm
Repository : epel
Summary : Library for compressed numerical arrays with high throughput R/W random access
URL : https://computation.llnl.gov/projects/floating-point-compression
License : BSD
Description : This is zfp, an open source C/C++ library for compressed numerical arrays
: that support high throughput read and write random access. zfp was written by
: Peter Lindstrom at Lawrence Livermore National Laboratory, and is loosely
: based on the algorithm described in the following paper:
:
: Peter Lindstrom
: "Fixed-Rate Compressed Floating-Point Arrays"
: IEEE Transactions on Visualization and Computer Graphics,
: 20(12):2674-2683, December 2014
: doi:10.1109/TVCG.2014.2346458
:
: zfp was originally designed for floating-point data only, but has been
: extended to also support integer data, and could for instance be used to
: compress images and quantized volumetric data. To achieve high compression
: ratios, zfp uses lossy but optionally error-bounded compression. Although
: bit-for-bit lossless compression of floating-point data is not always
: possible, zfp is usually accurate to within machine epsilon in near-lossless
: mode.
:
: zfp works best for 2D and 3D arrays that exhibit spatial coherence, such as
: smooth fields from physics simulations, images, regularly sampled terrain
: surfaces, etc. Although zfp also provides a 1D array class that can be used
: for 1D signals such as audio, or even unstructured floating-point streams,
: the compression scheme has not been well optimized for this use case, and
: rate and quality may not be competitive with floating-point compressors
: designed specifically for 1D streams.