Python interface to GPU-powered libraries
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/. 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.
This software is licensed under the BSD License. See the included LICENSE file for more information.
You can download the latest distribution from PyPI here: http://pypi.python.org/pypi/scikit-cuda
You can install scikit-cuda for yourself from the terminal by running:
pip install --user scikit-cuda
If you want to install it for all users on your machine, do:
pip install scikit-cudaOn Linux, do sudo pip install scikit-cuda.
This package was discovered in PyPI.