Pyculib - python bindings for NVIDIA CUDA libraries
Project description
Pyculib provides Python bindings to the following CUDA libraries:
These bindings are direct ports of those available in Anaconda Accelerate.
Documentation is located here
Installing
The easiest way to install Pyculib and get updates is by using the Anaconda Distribution
#> conda install pyculib
To compile from source, it is recommended to create a conda environment containing the following:
cffi
cudatoolkit
numpy
numba
pyculib_sorting
scipy
for instructions on how to do this see the conda documentation, specifically the section on managing environments.
Once a suitable environment is activated, installation achieved simply by running:
#> python setup.py install
and the installation can be tested with:
#> ./runtests.py
Documentation
Documentation is located here.
Building Documentation
It is also possible to build a local copy of the documentation from source. This requires GNU Make and sphinx (available via conda).
Documentation is stored in the doc folder, and should be built with:
#> make SPHINXOPTS=-Wn clean html
This ensures that the documentation renders without errors. If errors occur, they can all be seen at once by building with:
#> make SPHINXOPTS=-n clean html
However, these errors should all be fixed so that building with -Wn is possible prior to merging any documentation changes or updates.
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