How to Install and Uninstall python3-pycuda-dbg Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 18,2024

1. Install "python3-pycuda-dbg" package

Learn how to install python3-pycuda-dbg on Ubuntu 21.10 (Impish Indri)

$ sudo apt update $ sudo apt install python3-pycuda-dbg

2. Uninstall "python3-pycuda-dbg" package

Here is a brief guide to show you how to uninstall python3-pycuda-dbg on Ubuntu 21.10 (Impish Indri):

$ sudo apt remove python3-pycuda-dbg $ sudo apt autoclean && sudo apt autoremove

3. Information about the python3-pycuda-dbg package on Ubuntu 21.10 (Impish Indri)

Package: python3-pycuda-dbg
Architecture: amd64
Version: 2020.1~dfsg1-1build1
Priority: extra
Section: multiverse/debug
Source: pycuda
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian NVIDIA Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 19880
Depends: python3-dbg (<< 3.10), python3-pycuda (= 2020.1~dfsg1-1build1), python3-dbg (>= 3.9~), python3-numpy (>= 1:1.16.0~rc1), python3-numpy-abi9, libboost-python1.74.0 (>= 1.74.0), libboost-python1.74.0-py39, libboost-thread1.74.0 (>= 1.74.0), libc6 (>= 2.14), libcurand10, libgcc-s1 (>= 3.3.1), libnvidia-compute-465, libstdc++6 (>= 5.2)
Filename: pool/multiverse/p/pycuda/python3-pycuda-dbg_2020.1~dfsg1-1build1_amd64.deb
Size: 5494044
MD5sum: 193ae9f4b184d81c825072cd8f527538
SHA1: c732f71f156ea025c88ad34675d6dedd60f18f0a
SHA256: 076d4e2695135687db20c8679958155646bba20b0707e3f3a80447e0eb84a269
SHA512: 1f159c054eefea85a44b3f8c8a9ed8475aee39fa6191c02d82e96072c0d5fc8489bae9c276e85e14f4d34357929a9df432f5ea27c4e6c1bb7e2fce4bcb9b1f97
Homepage: http://mathema.tician.de/software/pycuda
Description-en: Python 3 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 for the Python 3 debug interpreter.
Description-md5: 2408be5275171c7291f7d0f275b7d393
Build-Ids: 120055486c88cd0c107debc4bd0853d47ea3d3eb d0ffe5d517fe66e6ce558f9a04473b0cce9fd60a