How to Install and Uninstall libmagma-dev Package on Ubuntu 21.04 (Hirsute Hippo)

Last updated: May 17,2024

1. Install "libmagma-dev" package

Please follow the instructions below to install libmagma-dev on Ubuntu 21.04 (Hirsute Hippo)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libmagma-dev
            
                    
    
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2. Uninstall "libmagma-dev" package

Please follow the instructions below to uninstall libmagma-dev on Ubuntu 21.04 (Hirsute Hippo):


    
        
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                sudo apt remove
            
                        
                libmagma-dev
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libmagma-dev package on Ubuntu 21.04 (Hirsute Hippo)

Package: libmagma-dev
Architecture: amd64
Version: 2.5.4+ds-2
Priority: optional
Section: multiverse/libdevel
Source: magma
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 485769
Filename: pool/multiverse/m/magma/libmagma-dev_2.5.4+ds-2_amd64.deb
Size: 67243668
MD5sum: 78b4e9ae8e2a0eadcbce884ff669bd4a
SHA1: 2f7fb71f860980cebe135a45c79c5cf4e1a1ef8d
SHA256: 61571281c6b89cb6314120543c436ff967543305c61515f492471847e69fb872
SHA512: 6293f0a21af9d193b0b2df4def2b976e3b228709f4188794472d96a7f13ef6bb19fec7848375c6db04125cb042686f85973b3da20e17c3061568d0544000b859
Homepage: https://icl.cs.utk.edu/magma/
Description-en: Matrix Algebra on GPU and Multicore Architectures (dev)
The MAGMA project aims to develop a dense linear algebra library similar to
LAPACK but for heterogeneous/hybrid architectures, starting with current
"Multicore+GPU" systems.
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The MAGMA research is based on the idea that, to address the complex challenges
of the emerging hybrid environments, optimal software solutions will themselves
have to hybridize, combining the strengths of different algorithms within a
single framework. Building on this idea, we aim to design linear algebra
algorithms and frameworks for hybrid manycore and GPU systems that can enable
applications to fully exploit the power that each of the hybrid components
offers.
.
This package contains the headers and the static libraries.
Description-md5: 8c96c9659ed332fd1cc18082bb49c285