How to Install and Uninstall python3-pycuda Package on Kali Linux

Last updated: December 29,2024

1. Install "python3-pycuda" package

Please follow the guidelines below to install python3-pycuda on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python3-pycuda
            
                    
    
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2. Uninstall "python3-pycuda" package

Please follow the guidance below to uninstall python3-pycuda on Kali Linux:


    
        
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                sudo apt remove
            
                        
                python3-pycuda
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the python3-pycuda package on Kali Linux

Package: python3-pycuda
Source: pycuda
Version: 2024.1~dfsg-1
Installed-Size: 3680
Maintainer: Debian NVIDIA Maintainers
Architecture: amd64
Depends: nvidia-cuda-toolkit, python3-appdirs (>= 1.4.0), python3-decorator (>= 3.2.0), python3-numpy (>= 1:1.22.0), python3-pytools, python3 (<< 3.13), python3 (>= 3.11~), python3-mako, python3-numpy-abi9, python3:any, libboost-python1.83.0 (>= 1.83.0), libboost-python1.83.0-py311, libboost-python1.83.0-py312, libboost-thread1.83.0 (>= 1.83.0), libc6 (>= 2.32), libcuda1 (>= 450.66) | libcuda.so.1 (>= 450.66), libcurand10, libgcc-s1 (>= 3.0), libstdc++6 (>= 13.1)
Recommends: python-pycuda-doc
Suggests: python3-matplotlib, python3-opengl, python3-pytest
Size: 509800
SHA256: ac4d56c0e70f7161094116568b7eddd27fedea5257e8fc9b84d70fa571c6fb90
SHA1: a36683135fcc4b644d71e4f70809637b42b30462
MD5sum: 61067a285d2a69d963d51c38e92a5896
Description: Python 3 module to access Nvidia‘s CUDA parallel computation API
PyCUDA lets you access Nvidia‘s CUDA parallel computation API from Python.
Several wrappers of the CUDA API already exist–so what’s so special about
PyCUDA?
* Object cleanup tied to lifetime of objects. This idiom, often called
RAII in C++, makes it much easier to write correct, leak- and crash-free
code. PyCUDA knows about dependencies, too, so (for example) it won’t
detach from a context before all memory allocated in it is also freed.
* Convenience. Abstractions like pycuda.driver.SourceModule and
pycuda.gpuarray.GPUArray make CUDA programming even more convenient than
with Nvidia’s C-based runtime.
* Completeness. PyCUDA puts the full power of CUDA’s driver API at your
disposal, if you wish.
* Automatic Error Checking. All CUDA errors are automatically translated
into Python exceptions.
* Speed. PyCUDA’s base layer is written in C++, so all the niceties
above are virtually free.
* Helpful Documentation.
.
This package contains Python 3 modules.
Description-md5:
Homepage: http://mathema.tician.de/software/pycuda
Section: contrib/python
Priority: optional
Filename: pool/contrib/p/pycuda/python3-pycuda_2024.1~dfsg-1_amd64.deb