How to Install and Uninstall libstarpu-contrib-1.4-4 Package on Kali Linux

Last updated: October 05,2024

1. Install "libstarpu-contrib-1.4-4" package

Please follow the guidelines below to install libstarpu-contrib-1.4-4 on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libstarpu-contrib-1.4-4
            
                    
    
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2. Uninstall "libstarpu-contrib-1.4-4" package

Please follow the steps below to uninstall libstarpu-contrib-1.4-4 on Kali Linux:


    
        
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                sudo apt remove
            
                        
                libstarpu-contrib-1.4-4
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the libstarpu-contrib-1.4-4 package on Kali Linux

Package: libstarpu-contrib-1.4-4
Source: starpu-contrib
Version: 1.4.3+dfsg-2
Installed-Size: 1987
Maintainer: Samuel Thibault
Architecture: amd64
Provides: libstarpu-any-1.4-4
Depends: libc6 (>= 2.34), libcublas12, libcudart12, libcusolver11, libcusparse12, libfxt2 (>= 0.3.13), libgcc-s1 (>= 3.4), libglpk40 (>= 4.59), libgomp1 (>= 4.9), libhwloc15 (>= 2.10.0), libnvidia-ml1 (>= 384) | libnvidia-ml.so.1 (>= 384), libpapi7.1, ocl-icd-libopencl1 | libopencl1
Conflicts: libstarpu-1.4-4
Size: 663028
SHA256: af5c8a9b773f5cdb82d9f130aafcee0a736f41d730ab8f251d8a3869178d7818
SHA1: 7dc23ce0074a440797515222933635e6278512d3
MD5sum: e273bd95d5cf88e44b7a73d95b03761d
Description: Task scheduler for heterogeneous multicore machines
StarPU is a runtime system that offers support for heterogeneous
multicore machines. While many efforts are devoted to design efficient
computation kernels for those architectures (e.g. to implement BLAS
kernels on GPUs or on Cell's SPUs), StarPU not only takes care of
offloading such kernels (and implementing data coherency across
the machine), but it also makes sure the kernels are executed as
efficiently as possible.
.
This package contains the main StarPU library
This "contrib" version is built against CUDA.
Description-md5:
Multi-Arch: same
Homepage: https://starpu.gitlabpages.inria.fr/
Section: contrib/libs
Priority: optional
Filename: pool/contrib/s/starpu-contrib/libstarpu-contrib-1.4-4_1.4.3+dfsg-2_amd64.deb