How to Install and Uninstall libcombblas2.0.0 Package on Kali Linux

Last updated: July 06,2024

1. Install "libcombblas2.0.0" package

Please follow the guidance below to install libcombblas2.0.0 on Kali Linux


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                libcombblas2.0.0
            
                    
    
    Copied

2. Uninstall "libcombblas2.0.0" package

This is a short guide on how to uninstall libcombblas2.0.0 on Kali Linux:


    
        
            $
        

        
            
                sudo apt remove
            
                        
                libcombblas2.0.0
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the libcombblas2.0.0 package on Kali Linux

Package: libcombblas2.0.0
Source: combblas (2.0.0-3)
Version: 2.0.0-3+b1
Installed-Size: 691
Maintainer: Debian Science Maintainers
Architecture: amd64
Depends: libc6 (>= 2.29), libgcc-s1 (>= 3.0), libopenmpi3 (>= 4.1.6), libstdc++6 (>= 13.1)
Size: 284460
SHA256: db80a76bbd21b580c00c2e7a5294b6df8bc9a57b5be5c60149712c00a46d6a5d
SHA1: 09ceed7c35bbc4a142a9a899a83da01513497f85
MD5sum: 2ac6df48e5e6c81ee452bf3d55699347
Description: 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:
Multi-Arch: same
Homepage: https://people.eecs.berkeley.edu/~aydin/CombBLAS/html/index.html
Section: libs
Priority: optional
Filename: pool/main/c/combblas/libcombblas2.0.0_2.0.0-3+b1_amd64.deb