scikit-cuda

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, as well as interfaces to select functions in the CULA Dense Toolkit. Both low-level wrapper functions similar to their C counterparts and high-level functions comparable to those in NumPy and Scipy are provided.

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.

The latest source code can be obtained from https://github.com/lebedov/scikit-cuda.

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.

If you use scikit-cuda in a scholarly publication, please cite it as follows:

@misc{givon_scikit-cuda_2019,
 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}}
}

See the included AUTHORS file for more information.

As of 2021, the CULA toolkit by EM Photonics no longer appears to be available.

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.

This software is licensed under the BSD License. See the included LICENSE file for more information.