CUDA Python is supported on all platforms that CUDA is supported. Specific dependencies are as follows:
Driver: Linux (450.80.02 or later) Windows (456.38 or later)
CUDA Toolkit 12.0 to 12.2
Python 3.8 to 3.11
Only the NVRTC redistributable component is required from the CUDA Toolkit. CUDA Toolkit Documentation Installation Guides can be used for guidance. Note that the NVRTC component in the Toolkit can be obtained via PiPy, Conda or Local Installer.
Installing from PyPI#
pip install cuda-python
Installing from Conda#
conda install -c nvidia cuda-python
Installing from Source#
Installing from source requires the latest CUDA Toolkit (CTK), matching the major.minor of CUDA Python. The installed package will still be compatible with all minor CTK versions.
Environment variable CUDA_HOME must be set to CTK root directory:
Remaining build and test dependencies are outlined in requirements.txt
To compile the extension in-place, run:
python setup.py build_ext --inplace
To compile for debugging the extension modules with gdb, pass the
argument to setup.py.
You can use
pip install -e .
to install the module as editible in your current Python environment (e.g. for testing of porting other libraries to use the binding).
Build the Docs#
conda env create -f docs_src/environment-docs.yml conda activate cuda-python-docs
Then compile and install
cuda-python following the steps above.
cd docs_src make html open build/html/index.html
Publish the Docs#
git checkout gh-pages cd docs_src make html cp -a build/html/. ../docs/