How to Install and Uninstall libcombblas-docs Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: April 29,2024

1. Install "libcombblas-docs" package

This is a short guide on how to install libcombblas-docs on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libcombblas-docs
            
                    
    
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2. Uninstall "libcombblas-docs" package

Please follow the steps below to uninstall libcombblas-docs on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                libcombblas-docs
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libcombblas-docs package on Ubuntu 20.10 (Groovy Gorilla)

Package: libcombblas-docs
Architecture: all
Version: 1.6.2-5build1
Multi-Arch: foreign
Priority: optional
Section: universe/libdevel
Source: combblas
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 280175
Recommends: libcombblas-dev
Filename: pool/universe/c/combblas/libcombblas-docs_1.6.2-5build1_all.deb
Size: 157111108
MD5sum: 7ba7d5e9efedeb43d2003c9b3299bcd2
SHA1: 6afefb33b02cd2286649b82d028589ea9dd2895b
SHA256: 5b56a5ecaf10523700de333cfae9a67c1d7dd74a4d77210fa54e0b7d00c82b38
SHA512: bb9ca3319e1f1f2de611b04125eb4daf402fae35e83a868e643c817943b4a2081635fad1ce0b396f0e88f030a63e10a4921a803e78f74683a66aaaf484f56562
Homepage: https://people.eecs.berkeley.edu/~aydin/CombBLAS/html/index.html
Description-en: an extensible parallel graph library for graph analytics (docs)
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 full HTML documentation for the CombBLAS API.
Description-md5: 10fdb310beb6f4139d1cf4aeab6ac436