SPORCO-CUDA provides GPU-accelerated versions of selected convolutional sparse coding algorithms in the SPORCO package. It is a component of SPORCO, and is subject to the same license, but is made available as an optional extension to avoid complicating the prerequisites and build/install procedure for the main part of SPORCO. If you use this software for published work, please cite it.
Documentation is available online at Read the Docs, or can be built from the root directory of the source distribution by the command
python setup.py build_sphinx
in which case the HTML documentation can be found in the
build/sphinx/html directory (the top-level document is
Scripts illustrating usage of the package can be found in the
examples directory of the source distribution. These examples can be run from the root directory of the package by, for example
To run these scripts prior to installing the package, it is necessary to build it in place, which involves the following steps:
Install the requirements described below
nvccis not already in the executable search path, add it; e.g
/usr/local/cuda-9.2/binis the path for CUDA compiler
sporco-cudapackage in place:
python setup.py build_ext --inplace
PYTHONPATHenvironment variable to include the root directory of the package. For example, in a
from the root directory of the package.
sporcopackage is not installed, create a symlink from the SPORCO-CUDA package root directory to the
sporcodirectory in the SPORCO package.
SPORCO-CUDA is part of the SPORCO package and is distributed with the same 3-Clause BSD license; see the
LICENSE file for details.