How to Install and Uninstall libblosc1 Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: December 23,2024

1. Install "libblosc1" package

In this section, we are going to explain the necessary steps to install libblosc1 on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libblosc1
            
                    
    
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2. Uninstall "libblosc1" package

This guide let you learn how to uninstall libblosc1 on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                libblosc1
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libblosc1 package on Ubuntu 20.10 (Groovy Gorilla)

Package: libblosc1
Architecture: amd64
Version: 1.17.1+ds1-1
Priority: optional
Section: universe/libs
Source: c-blosc
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian QA Group
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 97
Depends: libc6 (>= 2.14), liblz4-1 (>= 0.0~r130), libsnappy1v5 (>= 1.1.7), libzstd1 (>= 1.3.2), zlib1g (>= 1:1.1.4)
Filename: pool/universe/c/c-blosc/libblosc1_1.17.1+ds1-1_amd64.deb
Size: 32248
MD5sum: 0aef1354389bb062afe51400587b7e02
SHA1: 1c158729b2fdaf03eea53085e2faefec06a5183b
SHA256: 6de0edc9ebfd94f8326f3e28da6d1de651e3bd7b4f8b771388c94db3fe802237
SHA512: d887e47768ee9f5c503e4ea485a1f11f73357fe27d48f2096126dec7a5cd2c168b70d66a4cf681d2501e4418fa14bc133a0ccec48fcdc5306bd630187a133312
Homepage: http://blosc.org/
Description-en: high performance meta-compressor optimized for binary data
Blosc is a high performance compressor optimized for binary data. It has been
designed to transmit data to the processor cache faster than the traditional,
non-compressed, direct memory fetch approach via a memcpy() OS call. Blosc is
meant not only to reduce the size of large datasets on-disk or in-memory, but
also to accelerate memory-bound computations.
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It uses the blocking technique to reduce activity on the memory bus as much
as possible. In short, this technique works by dividing datasets in blocks
that are small enough to fit in caches of modern processors and perform
compression / decompression there. It also leverages, if available, SIMD
instructions (SSE2) and multi-threading capabilities of CPUs, in order to
accelerate the compression / decompression process to a maximum.
Description-md5: 00198534c7d52daa250235b07fd3d873
Task: ubuntustudio-video, ubuntustudio-graphics