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ActivePython
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pypm install pyopencl

How to install pyopencl

  1. Download and install ActivePython
  2. Open Command Prompt
  3. Type pypm install pyopencl
 Python 2.7Python 3.2Python 3.3
Windows (32-bit)
2013.1Never BuiltWhy not?
2012.1 Failed View build log
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Windows (64-bit)
2013.1Never BuiltWhy not?
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Mac OS X (10.5+)
2012.1
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2012.1 Available View build log
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2011.1beta3 Available View build log
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2012.1
2013.1Never BuiltWhy not?
2012.1 Available View build log
2011.2 Available View build log
2011.1.2 Available View build log
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Linux (32-bit)
2013.1 Failed View build log
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2013.1Never BuiltWhy not?
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Linux (64-bit)
2013.1 Failed View build log
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2011.1 Failed View build log
2011.1beta3 Failed View build log
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2011.1beta Failed View build log
0.92 Failed View build log
0.91.5 Failed View build log
2013.1Never BuiltWhy not?
2012.1 Failed View build log
2011.2 Failed View build log
2011.1.2 Failed View build log
2011.1.1 Failed View build log
2011.1 Failed View build log
2011.1beta3 Failed View build log
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License
MIT
Depended by
Lastest release
version 2013.1 on Jul 7th, 2013

PyOpenCL lets you access GPUs and other massively parallel compute devices from Python. It tries to offer computing goodness in the spirit of its sister project 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.
  • Completeness. PyOpenCL puts the full power of OpenCL's API at your disposal, if you wish. Every obscure get_info() query and all CL calls are accessible.
  • Automatic Error Checking. All CL errors are automatically translated into Python exceptions.
  • Speed. PyOpenCL's base layer is written in C++, so all the niceties above are virtually free.
  • Helpful and complete Documentation as well as a Wiki.
  • Liberal license. PyOpenCL is open-source under the MIT license and free for commercial, academic, and private use.
  • Broad support. PyOpenCL was tested and works with Apple's, AMD's, and Nvidia's CL implementations.

To use PyOpenCL, you just need numpy <http://numpy.org> and an OpenCL implementation. (See this howto for how to get one.)

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Last updated Jul 7th, 2013

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