Python interface to GPU-powered libraries
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.. image:: https://raw.githubusercontent.com/lebedov/scikit-cuda/master/docs/source/_static/logo.png :alt: scikit-cuda
Package Description
scikit-cuda provides Python interfaces to many of the functions in the CUDA device/runtime, CUBLAS, CUFFT, and CUSOLVER libraries distributed as part of NVIDIA's
CUDA Programming Toolkit <http://www.nvidia.com/cuda/>_, as well as interfaces to select functions in the CULA Dense Toolkit <http://www.culatools.com/dense>_. Both low-level wrapper functions similar to their C counterparts and high-level functions comparable to those in NumPy and Scipy <http://www.scipy.org>_ are provided.
.. image:: https://zenodo.org/badge/doi/10.5281/zenodo.3229433.svg :target: http://dx.doi.org/10.5281/zenodo.3229433 :alt: 0.5.3 .. image:: https://img.shields.io/pypi/v/scikit-cuda.svg :target: https://pypi.python.org/pypi/scikit-cuda :alt: Latest Version .. image:: https://img.shields.io/pypi/dm/scikit-cuda.svg :target: https://pypi.python.org/pypi/scikit-cuda :alt: Downloads .. image:: http://prime4commit.com/projects/102.svg :target: http://prime4commit.com/projects/102 :alt: Support the project .. image:: https://www.openhub.net/p/scikit-cuda/widgets/projectthinbadge?format=gif :target: https://www.openhub.net/p/scikit-cuda?ref=Thin+badge :alt: Open Hub
Documentation
Package documentation is available at
<http://scikit-cuda.readthedocs.org/>_. Many of the high-level functions have examples in their docstrings. More illustrations of how to use both the wrappers and high-level functions can be found in the `demos/ and tests/ subdirectories.
Development
The latest source code can be obtained from _.
When submitting bug reports or questions via the
issue tracker _, please include the following information:
- Python version.
- OS platform.
- CUDA and PyCUDA version.
- Version or git revision of scikit-cuda.
Citing
If you use scikit-cuda in a scholarly publication, please cite it as follows: ::
@misc{givonscikit-cuda2019, author = {Lev E. Givon and Thomas Unterthiner and N. Benjamin Erichson and David Wei Chiang and Eric Larson and Luke Pfister and Sander Dieleman and Gregory R. Lee and Stefan van der Walt and Bryant Menn and Teodor Mihai Moldovan and Fr\'{e}d\'{e}ric Bastien and Xing Shi and Jan Schl\"{u}ter and Brian Thomas and Chris Capdevila and Alex Rubinsteyn and Michael M. Forbes and Jacob Frelinger and Tim Klein and Bruce Merry and Nate Merill and Lars Pastewka and Li Yong Liu and S. Clarkson and Michael Rader and Steve Taylor and Arnaud Bergeron and Nikul H. Ukani and Feng Wang and Wing-Kit Lee and Yiyin Zhou}, title = {scikit-cuda 0.5.3: a {Python} interface to {GPU}-powered libraries}, month = May, year = 2019, doi = {10.5281/zenodo.3229433}, url = {http://dx.doi.org/10.5281/zenodo.3229433}, note = {\url{http://dx.doi.org/10.5281/zenodo.3229433}} }
Authors & Acknowledgments
See the included AUTHORS _ file for more information.
Note Regarding CULA Availability
As of 2021, the CULA toolkit by EM Photonics _ no longer appears to be available.
Related
Python wrappers for cuDNN _ by Hannes Bretschneider are available here _.
ArrayFire is a free library containing many GPU-based routines with an officially supported Python interface .
License
This software is licensed under the BSD License _. See the included LICENSE 
