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

Last updated: November 26,2024

1. Install "python-pycuda-dbg" package

This tutorial shows how to install python-pycuda-dbg on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python-pycuda-dbg
            
                    
    
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2. Uninstall "python-pycuda-dbg" package

Here is a brief guide to show you how to uninstall python-pycuda-dbg on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                python-pycuda-dbg
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python-pycuda-dbg package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: python-pycuda-dbg
Priority: extra
Section: multiverse/debug
Installed-Size: 16013
Maintainer: Ubuntu Developers
Original-Maintainer: Tomasz Rybak
Architecture: amd64
Source: pycuda
Version: 2016.1-1
Depends: python-pycuda (= 2016.1-1), python-dbg (<< 2.8), 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), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (>= 2.7~)
Filename: pool/multiverse/p/pycuda/python-pycuda-dbg_2016.1-1_amd64.deb
Size: 4648180
MD5sum: f5e8749979661823a30ce46dd7f11aee
SHA1: 2bb0ac4f0aacdff2a0b27ab4f6ab1fb9c76b503d
SHA256: 4112740a5fd5b031c17abf345dcd66ca5157f0b4dcd7eee48d4924dbf7197036
Description-en: Python module to access Nvidia‘s CUDA API (debug extensions)
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 debug extensions build for the Python debug interpreter.
Description-md5: ae08beb79e6eee13bd1e5931765375b1
Homepage: http://mathema.tician.de/software/pycuda
Build-Ids: 9b74d6fe7e813f4bf06ed96dd83e777bdea290b0 bedb25e4e27701f8c1312487045667ce4b7c469b
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu