How to Install and Uninstall libcombblas1.16.0 Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: December 24,2024

1. Install "libcombblas1.16.0" package

This guide let you learn how to install libcombblas1.16.0 on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libcombblas1.16.0
            
                    
    
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2. Uninstall "libcombblas1.16.0" package

Please follow the instructions below to uninstall libcombblas1.16.0 on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                libcombblas1.16.0
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libcombblas1.16.0 package on Ubuntu 20.10 (Groovy Gorilla)

Package: libcombblas1.16.0
Architecture: amd64
Version: 1.6.2-5build1
Multi-Arch: same
Priority: optional
Section: universe/libs
Source: combblas
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 702
Depends: libc6 (>= 2.14), libgcc-s1 (>= 3.0), libopenmpi3 (>= 4.0.3~rc4), libstdc++6 (>= 5.2)
Filename: pool/universe/c/combblas/libcombblas1.16.0_1.6.2-5build1_amd64.deb
Size: 272368
MD5sum: 53a49a008286cea7f1cae4100eda0ba7
SHA1: fde76b9c4ee7721285ded7073bfcfcbb880a81f9
SHA256: c6b2057e61d187a1767b725c9154fbb15a0e9bf1e1a71ccb69305719991e797e
SHA512: fe814054c14da789fc22e481b2f0da6e8f7cd47fb69b585ebcc8153f99c93bc7696e36137f09aae0c956d86dff935e7cc4e349b8dee7a31fb82079587c8fb70b
Homepage: https://people.eecs.berkeley.edu/~aydin/CombBLAS/html/index.html
Description-en: an extensible parallel graph library for graph analytics
The Combinatorial BLAS (CombBLAS) is an extensible distributed-memory
parallel graph library offering a small but powerful set of linear
algebra primitives specifically targeting graph analytics.
.
- The Combinatorial BLAS development influences the Graph BLAS
standardization process.
- It achieves scalability via its two dimensional distribution and
coarse-grained parallelism.
- CombBLAS powers HipMCL, a highly-scalable parallel implementation of
the Markov Cluster Algorithm (MCL).
- Operations among sparse matrices and vectors use arbitrary user
defined semirings.
.
This package provides the combblas shared library.
Description-md5: 40b7560544e0c13716535d69a7bfc105