How to Install and Uninstall python-pycuda-doc Package on Kali Linux

Last updated: May 20,2024

1. Install "python-pycuda-doc" package

Here is a brief guide to show you how to install python-pycuda-doc on Kali Linux


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                python-pycuda-doc
            
                    
    
    Copied

2. Uninstall "python-pycuda-doc" package

Please follow the guidelines below to uninstall python-pycuda-doc on Kali Linux:


    
        
            $
        

        
            
                sudo apt remove
            
                        
                python-pycuda-doc
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the python-pycuda-doc package on Kali Linux

Package: python-pycuda-doc
Source: pycuda
Version: 2024.1~dfsg-1
Installed-Size: 1512
Maintainer: Debian NVIDIA Maintainers
Architecture: all
Depends: fonts-mathjax, libjs-mathjax, libjs-sphinxdoc (>= 7.2.2)
Recommends: nvidia-cuda-doc, python-mako-doc, python3-doc
Suggests: python3-pycuda
Size: 183636
SHA256: f4fb7885ce2bac7eed8420cb50a1233e0ce18f0848cddd6b64b2dcdecf1dad28
SHA1: 87092a24c059749cb0100ade7b55c82172098889
MD5sum: abd954ac88e680f534be9dc926dc2466
Description: module to access Nvidia‘s CUDA computation API (documentation)
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 HTML documentation and example scripts.
Description-md5:
Multi-Arch: foreign
Homepage: http://mathema.tician.de/software/pycuda
Tag: role::documentation
Section: contrib/doc
Priority: optional
Filename: pool/contrib/p/pycuda/python-pycuda-doc_2024.1~dfsg-1_all.deb