Skip to main content

Python wrapper for OpenCL

Project description

Gitlab Build Status Github Build Status Python Package Index Release Page

(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 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.

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:

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-2020.1.tar.gz (345.7 kB view details)

Uploaded Source

Built Distributions

pyopencl-2020.1-cp38-cp38-manylinux1_x86_64.whl (723.7 kB view details)

Uploaded CPython 3.8

pyopencl-2020.1-cp37-cp37m-manylinux1_x86_64.whl (728.3 kB view details)

Uploaded CPython 3.7m

pyopencl-2020.1-cp36-cp36m-manylinux1_x86_64.whl (728.2 kB view details)

Uploaded CPython 3.6m

pyopencl-2020.1-cp35-cp35m-manylinux1_x86_64.whl (728.2 kB view details)

Uploaded CPython 3.5m

pyopencl-2020.1-cp27-cp27mu-manylinux1_x86_64.whl (726.7 kB view details)

Uploaded CPython 2.7mu

pyopencl-2020.1-cp27-cp27m-manylinux1_x86_64.whl (726.7 kB view details)

Uploaded CPython 2.7m

File details

Details for the file pyopencl-2020.1.tar.gz.

File metadata

  • Download URL: pyopencl-2020.1.tar.gz
  • Upload date:
  • Size: 345.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.44.1 CPython/3.7.7

File hashes

Hashes for pyopencl-2020.1.tar.gz
Algorithm Hash digest
SHA256 7513f7054f4eeb5361de1f5113883145fc67dbabde73a2148f221ae05af4d22c
MD5 bce86ca64cd5186d19f4ab008eeabd58
BLAKE2b-256 41a1884bc4c8d45cf4789ceba119e5f7f59e0b7ab7029504aa2166d933956b8f

See more details on using hashes here.

File details

Details for the file pyopencl-2020.1-cp38-cp38-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyopencl-2020.1-cp38-cp38-manylinux1_x86_64.whl
  • Upload date:
  • Size: 723.7 kB
  • Tags: CPython 3.8
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.7

File hashes

Hashes for pyopencl-2020.1-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 18dd3f652beb94004854de0e086aa1f3ad8ae95a683d52a5ee2d86349da522d5
MD5 d5af7bc22f5d6f714d3c60668c3549c2
BLAKE2b-256 04c45b41f6bfd1ca25e3cd52fca170f69d9633a1f483559716787e6d036a0eeb

See more details on using hashes here.

File details

Details for the file pyopencl-2020.1-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyopencl-2020.1-cp37-cp37m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 728.3 kB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.7

File hashes

Hashes for pyopencl-2020.1-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 9eb2e99ca5de8c6fda4bacf3fb5f5de0fdfa0da0f40ed6966fd913c30ac407b3
MD5 4125e45319678ebea295dcd060ab4985
BLAKE2b-256 2935cf25b3af34c49e83667d2575fbccb19b34a16d5e49f9f352befca45f19ce

See more details on using hashes here.

File details

Details for the file pyopencl-2020.1-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyopencl-2020.1-cp36-cp36m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 728.2 kB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.7

File hashes

Hashes for pyopencl-2020.1-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 7fe36afbb060839570d216c5cae1c023e6b70f7852a9177004cfbf0cc6ea7d79
MD5 5460e27a00949ed554ed491c068ab74d
BLAKE2b-256 0dabaa0ec8018066a7a70a8a7d5e342cce6d5f35058bed7c22fb6ce78ab7c963

See more details on using hashes here.

File details

Details for the file pyopencl-2020.1-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyopencl-2020.1-cp35-cp35m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 728.2 kB
  • Tags: CPython 3.5m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.7

File hashes

Hashes for pyopencl-2020.1-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 464452d3cebd9b0e4b5ade113e85671a1924b9c4f1907060e7fb05c3e7a744fd
MD5 dc00374e01eb32f5c63cc6065d35d679
BLAKE2b-256 17d4a451cc58e8158249aa0822886970cb5f36a523e05e092f3fbc50161f5e97

See more details on using hashes here.

File details

Details for the file pyopencl-2020.1-cp27-cp27mu-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyopencl-2020.1-cp27-cp27mu-manylinux1_x86_64.whl
  • Upload date:
  • Size: 726.7 kB
  • Tags: CPython 2.7mu
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.7

File hashes

Hashes for pyopencl-2020.1-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 4d88105f5bfcc33c3b15a4d91d11b0f6a00c81631d576085d4be5f19faf85c6d
MD5 74d4b74b7a0fb242ce348cc61489992a
BLAKE2b-256 6220d66226f835867b0ac4492de4e63a140374cba798296f0f29528c834ba942

See more details on using hashes here.

File details

Details for the file pyopencl-2020.1-cp27-cp27m-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyopencl-2020.1-cp27-cp27m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 726.7 kB
  • Tags: CPython 2.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.7

File hashes

Hashes for pyopencl-2020.1-cp27-cp27m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 0990fe7fe0fb9f7855c570492aa42c9e4babd390fd4f2177831254ea1e1c05ac
MD5 393856e0767d17caf5ded90464823db0
BLAKE2b-256 53a2388b463512db44b9ea3648b666becbb2c2a30dff35e04f7ab353d7498858

See more details on using hashes here.

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