How to Install and Uninstall libgloo-cuda-0 Package on Kali Linux

Last updated: May 17,2024

Deprecated! Installation of this package may no longer be supported.

1. Install "libgloo-cuda-0" package

Please follow the steps below to install libgloo-cuda-0 on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libgloo-cuda-0
            
                    
    
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2. Uninstall "libgloo-cuda-0" package

Please follow the instructions below to uninstall libgloo-cuda-0 on Kali Linux:


    
        
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                sudo apt remove
            
                        
                libgloo-cuda-0
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the libgloo-cuda-0 package on Kali Linux

Package: libgloo-cuda-0
Source: gloo-cuda
Version: 0.0~git20230117.1090929-2
Installed-Size: 2545
Maintainer: Debian Deep Learning Team
Architecture: amd64
Replaces: libgloo0
Depends: libc6 (>= 2.34), libcudart12, libgcc-s1 (>= 3.0), libhiredis0.14 (>= 0.14.0), libibverbs1 (>= 1.1.6), libnccl2 (>= 2.16.5), libopenmpi3 (>= 4.1.5), libstdc++6 (>= 12)
Conflicts: libgloo0
Size: 444764
SHA256: 869ca5c6f080c63689a27abac3e1e4dc95aef6d8e1f618259104ba31d194a312
SHA1: 3acc719a85fc6d5bc4134ccef9abd193821f9032
MD5sum: 01322a4b46ee941e9073c58605b288cf
Description: Collective communications library (shared object)
Gloo is a collective communications library. It comes with a number of
collective algorithms useful for machine learning applications. These
include a barrier, broadcast, and allreduce.
.
Transport of data between participating machines is abstracted so that
IP can be used at all times, or InifiniBand (or RoCE) when available.
In the latter case, if the InfiniBand transport is used, GPUDirect can
be used to accelerate cross machine GPU-to-GPU memory transfers.
.
Where applicable, algorithms have an implementation that works with system
memory buffers, and one that works with NVIDIA GPU memory buffers. In the
latter case, it is not necessary to copy memory between host and device;
this is taken care of by the algorithm implementations.
.
This package ships the shared object for Gloo.
Description-md5:
Homepage: https://github.com/facebookincubator/gloo
Section: contrib/libs
Priority: optional
Filename: pool/contrib/g/gloo-cuda/libgloo-cuda-0_0.0~git20230117.1090929-2_amd64.deb