How to Install and Uninstall python3-pycuda Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: May 14,2024

1. Install "python3-pycuda" package

Please follow the instructions below to install python3-pycuda on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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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 guidelines below to uninstall python3-pycuda on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                python3-pycuda
            
                    
    
    Copied


    
        
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the python3-pycuda package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: python3-pycuda
Priority: optional
Section: multiverse/python
Installed-Size: 1859
Maintainer: Ubuntu Developers
Original-Maintainer: Tomasz Rybak
Architecture: amd64
Source: pycuda
Version: 2016.1-1
Replaces: python-pycuda-headers
Depends: libboost-python1.58.0, libboost-thread1.58.0, libc6 (>= 2.14), libcuda-5.5-1, libcurand7.5 (>= 4.0), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~), python3-appdirs (>= 1.4.0), python3-decorator (>= 3.2.0), python3-pytools, nvidia-cuda-toolkit
Recommends: python-pycuda-doc, python3-mako
Suggests: python3-pytest, python3-opengl, python3-matplotlib, python3-pycuda-dbg
Filename: pool/multiverse/p/pycuda/python3-pycuda_2016.1-1_amd64.deb
Size: 305544
MD5sum: e4f8e3fb210f874ca5cea867588f3d49
SHA1: bad8865ef06912fdc2722b07929a2f227dac7d10
SHA256: 5ea5cc2232706d0bf8dd888ab4c73779a3f800658589177601a4bc8cbdf47f72
Description-en: 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: 4f446cb70e3ba6723eaae62a94efb36c
Homepage: http://mathema.tician.de/software/pycuda
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu