pygpu 0.2.0a-629-4 source package in Ubuntu

Changelog

pygpu (0.2.0a-629-4) unstable; urgency=low

  * Team upload.
  * Rebuild to add Python 2.7 support

pygpu (0.2.0a-629-3) unstable; urgency=low

  * switch from python-central to dh_python2 (Closes: #616967)
  * debian/control:
    - switch to my Debian address
    - drop python-central
    - bump debhelper dependency to 7.0.50
    - add version to python dependency
    - bump Standards-Version to 3.9.1 (no changes needed)
    - change XS-Python-Version to X-Python-Version
    - drop XB-Python-Version
    - add Breaks: ${python:Breaks}
    - add Provides: ${python:Provides}
  * add debian/source/format
  * add README.txt to new debian/python-pygpu.docs
  * add main.py, pygpu_test.py and data directory to new
    debian/python-pygpu.examples
  * debian/compat:
    - bump debhelper compatibility to 7
  * debian/rules:
    - switch to simplified dh rules
    - don't compress .py files
    - add --install-layout=deb to setup.py install call
  * debian/copyright:
    - add myself to copyright holders of the Debian packaging
 -- Ubuntu Archive Auto-Sync <email address hidden>   Tue,  10 May 2011 12:37:52 +0000

Upload details

Uploaded by:
Ubuntu Archive Auto-Sync
Uploaded to:
Oneiric
Original maintainer:
Debian Python Modules Team
Architectures:
all
Section:
python
Urgency:
Low Urgency

See full publishing history Publishing

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Builds

Oneiric: [FULLYBUILT] i386

Downloads

File Size SHA-256 Checksum
pygpu_0.2.0a-629.orig.tar.gz 196.3 KiB 92d8f73358682fd9365f4d8755060ae74c0c7851bd25ec3f167e9053fcf707de
pygpu_0.2.0a-629-4.diff.gz 2.5 KiB b2236bb71ef6336d0bb07cb2e4ef356489847576ae4073cdb028fefc1eb3b0c8
pygpu_0.2.0a-629-4.dsc 1.9 KiB 884d741c23729e4f2969ea1aef708d2d5c38d457fffb1c55b5a91fb396c695eb

Available diffs

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Binary packages built by this source

python-pygpu: embedded language for programming GPU using Python

 PyGPU is a compiler that lets you write image processing programs in
 Python that execute on the graphics processing unit (GPU) present in
 modern graphics cards. This enables image processing algorithms to
 take advantage of the performance of the GPU. In some applications,
 performance increases approach an order of magnitude, compared to CPUs.