Skip to main content

Python wrapper for OpenCL

Project description

PyOpenCL: Pythonic Access to OpenCL, with Arrays and Algorithms

.. image::
.. image::
(Also: `Travis CI <>`_ to build binary wheels for releases, see `#264 <>`_)

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
`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.

Simple 4-step `install instructions <>`_
using Conda on Linux and macOS (that also install a working OpenCL implementation!)
can be found in the `documentation <>`_.

What you'll need if you do *not* want to use the convenient instructions above and
instead build from source:

* gcc/g++ new enough to be compatible with pybind11
(see their `FAQ <>`_)
* `numpy <>`_, and
* an OpenCL implementation. (See this `howto <>`_ for how to get one.)

Places on the web related to PyOpenCL:

* `Python package index <>`_ (download releases)

* `Documentation <>`_ (read how things work)
* `Conda Forge <>`_ (download binary packages for Linux, macOS, Windows)
* `C. Gohlke's Windows binaries <>`_ (download Windows binaries)
* `Github <>`_ (get latest source code, file bugs)
* `Wiki <>`_ (read installation tips, get examples, read FAQ)

Project details

Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyopencl-2018.2.5.tar.gz (340.7 kB view hashes)

Uploaded Source

Built Distributions

pyopencl-2018.2.5-cp37-cp37m-manylinux1_x86_64.whl (723.2 kB view hashes)

Uploaded CPython 3.7m

pyopencl-2018.2.5-cp37-cp37m-manylinux1_i686.whl (694.5 kB view hashes)

Uploaded CPython 3.7m

pyopencl-2018.2.5-cp36-cp36m-manylinux1_x86_64.whl (723.1 kB view hashes)

Uploaded CPython 3.6m

pyopencl-2018.2.5-cp36-cp36m-manylinux1_i686.whl (694.7 kB view hashes)

Uploaded CPython 3.6m

pyopencl-2018.2.5-cp35-cp35m-manylinux1_x86_64.whl (723.1 kB view hashes)

Uploaded CPython 3.5m

pyopencl-2018.2.5-cp35-cp35m-manylinux1_i686.whl (694.7 kB view hashes)

Uploaded CPython 3.5m

pyopencl-2018.2.5-cp34-cp34m-manylinux1_x86_64.whl (723.0 kB view hashes)

Uploaded CPython 3.4m

pyopencl-2018.2.5-cp34-cp34m-manylinux1_i686.whl (694.6 kB view hashes)

Uploaded CPython 3.4m

pyopencl-2018.2.5-cp27-cp27mu-manylinux1_x86_64.whl (722.5 kB view hashes)

Uploaded CPython 2.7mu

pyopencl-2018.2.5-cp27-cp27mu-manylinux1_i686.whl (694.3 kB view hashes)

Uploaded CPython 2.7mu

pyopencl-2018.2.5-cp27-cp27m-manylinux1_x86_64.whl (722.5 kB view hashes)

Uploaded CPython 2.7m

pyopencl-2018.2.5-cp27-cp27m-manylinux1_i686.whl (694.3 kB view hashes)

Uploaded CPython 2.7m

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page