How to Install and Uninstall libcusparse7.5 Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: May 20,2024

1. Install "libcusparse7.5" package

Please follow the instructions below to install libcusparse7.5 on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libcusparse7.5
            
                    
    
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2. Uninstall "libcusparse7.5" package

Please follow the guidelines below to uninstall libcusparse7.5 on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                libcusparse7.5
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libcusparse7.5 package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: libcusparse7.5
Priority: extra
Section: multiverse/libs
Installed-Size: 36097
Maintainer: Ubuntu Developers
Original-Maintainer: Debian NVIDIA Maintainers
Architecture: amd64
Source: nvidia-cuda-toolkit
Version: 7.5.18-0ubuntu1
Depends: libc6 (>= 2.3.3), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1)
Filename: pool/multiverse/n/nvidia-cuda-toolkit/libcusparse7.5_7.5.18-0ubuntu1_amd64.deb
Size: 19194870
MD5sum: 732f572684614825dc7edac8168ba2bf
SHA1: 78e8e008bb73c3d1ba5d251f459c0881c66b8f6d
SHA256: fe252d8d12d7d58f49bc6bf5a5191693e3f055c530b680358c8f519232229aa1
Description-en: NVIDIA cuSPARSE Library
The Compute Unified Device Architecture (CUDA) enables NVIDIA
graphics processing units (GPUs) to be used for massively parallel
general purpose computation.
.
The cuSPARSE library contains a set of basic linear algebra subroutines used
for handling sparse matrices. It is implemented on top of the NVIDIA CUDA
runtime and is designed to be called from C and C++. The library routines can
be classified into four categories:
* Level 1: operations between a vector in sparse format and a vector in dense
format
* Level 2: operations between a matrix in sparse format and a vector in dense
format
* Level 3: operations between a matrix in sparse format and a set of vectors
in dense format
* Conversion: operations that allow conversion between different matrix
formats
.
This package contains the cuSPARSE runtime library.
Description-md5: 12835bf1c971845122d660784efe714a
Multi-Arch: same
Homepage: http://www.nvidia.com/CUDA
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu