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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 <https://mathema.tician.de/software/pycuda>__:
Object cleanup tied to lifetime of objects. This idiom, often
called RAII <https://en.wikipedia.org/wiki/Resource_Acquisition_Is_Initialization>__
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 <https://documen.tician.de/pyopencl>__
as well as a Wiki <https://wiki.tiker.net/PyOpenCL>__.
Liberal license. PyOpenCL is open-source under the
MIT license <https://en.wikipedia.org/wiki/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.
Simple 4-step install instructions <https://documen.tician.de/pyopencl/misc.html#installation>__
using Conda on Linux and macOS (that also install a working OpenCL implementation!)
can be found in the documentation <https://documen.tician.de/pyopencl/>__.
What you'll need if you do not want to use the convenient instructions above and instead build from source:
numpy <https://numpy.org>__, andhowto <https://wiki.tiker.net/OpenCLHowTo>__
for how to get one.)Documentation <https://documen.tician.de/pyopencl>__
(read how things work)Python package index <https://pypi.python.org/pypi/pyopencl>__
(download releases, including binary wheels for Linux, macOS, Windows)Conda Forge <https://anaconda.org/conda-forge/pyopencl>__
(download binary packages for Linux, macOS, Windows)Github <https://github.com/inducer/pyopencl>__
(get latest source code, file bugs)FAQs
Python wrapper for OpenCL
We found that pyopencl demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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