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 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

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.

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.


GitHub - lebedov/scikit-cuda: Python interface to GPU-powered libraries
Python interface to GPU-powered libraries. Contribute to lebedov/scikit-cuda development by creating an account on GitHub.