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 free and standard versions of 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/.
The latest source code can be obtained from https://github.com/lebedov/scikit-cuda.
If you use scikit-cuda in a scholarly publication, please cite it as follows:
@misc{givon_scikit-cuda_2015,
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
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
Lars Pastewka and
Steve Taylor and
Feng Wang and
Yiyin Zhou},
title = {scikit-cuda 0.5.1: a {Python} interface to {GPU}-powered libraries},
month = December,
year = 2015,
doi = {10.5281/zenodo.40565},
url = {http://dx.doi.org/10.5281/zenodo.40565},
note = {\url{http://dx.doi.org/10.5281/zenodo.40565}}
}
See the included AUTHORS file for more information.
Python wrappers for cuDNN by Hannes Bretschneider are available here.
This software is licensed under the BSD License. See the included LICENSE file for more information.