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Metadata-Version: 2.1
Name: pyopencl
Version: 2025.1
Summary: Python wrapper for OpenCL
Author-Email: Andreas Kloeckner <inform@tiker.net>
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Project-URL: Documentation, https://documen.tician.de/pyopencl
Project-URL: Homepage, https://mathema.tician.de/software/pyopencl
Project-URL: Repository, https://github.com/inducer/pyopencl
Requires-Python: ~=3.8
Requires-Dist: importlib-resources; python_version < "3.9"
Requires-Dist: numpy
Requires-Dist: platformdirs>=2.2
Requires-Dist: pytools>=2024.1.5
Requires-Dist: oclgrind-binary-distribution>=18.3; extra == "oclgrind"
Requires-Dist: pocl-binary-distribution>=1.2; extra == "pocl"
Requires-Dist: ruff; extra == "test"
Requires-Dist: mako; extra == "test"
Requires-Dist: mypy; extra == "test"
Requires-Dist: pylint; extra == "test"
Requires-Dist: pytest>=7; extra == "test"
Provides-Extra: oclgrind
Provides-Extra: pocl
Provides-Extra: test
Description-Content-Type: text/x-rst
PyOpenCL: Pythonic Access to OpenCL, with Arrays and Algorithms
===============================================================
.. |badge-gitlab-ci| image:: https://gitlab.tiker.net/inducer/pyopencl/badges/main/pipeline.svg
:alt: Gitlab Build Status
:target: https://gitlab.tiker.net/inducer/pyopencl/commits/main
.. |badge-github-ci| image:: https://github.com/inducer/pyopencl/workflows/CI/badge.svg?branch=main&event=push
:alt: Github Build Status
:target: https://github.com/inducer/pyopencl/actions?query=branch%3Amain+workflow%3ACI+event%3Apush
.. |badge-pypi| image:: https://badge.fury.io/py/pyopencl.svg
:alt: Python Package Index Release Page
:target: https://pypi.org/project/pyopencl/
.. |badge-zenodo| image:: https://zenodo.org/badge/1575307.svg
:alt: Zenodo DOI for latest release
:target: https://zenodo.org/badge/latestdoi/1575307
|badge-gitlab-ci| |badge-github-ci| |badge-pypi| |badge-zenodo|
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:
* g++/clang new enough to be compatible with nanobind (specifically, full support of C++17 is needed)
* `numpy <https://numpy.org>`__, and
* an OpenCL implementation. (See this `howto <https://wiki.tiker.net/OpenCLHowTo>`__
for how to get one.)
Links
-----
* `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)
|
