Installation guide

If GPU acceleration is required, make sure the CUDA toolkit is installed first.

The C library

The processing function library is compiled from source using CMake.

From the top-level directory, run the following commands to compile and install the library:

mkdir build
cd build
cmake .. [OPTIONS]
make -j8
make install

The CMake options are as follows:

• Use -DFIND_CUDA=OFF|ON to specify whether or not CUDA should be used. The default value for this is ON.

• Use -DCUDA_ARCH="x.y" to compile CUDA code for the specified GPU architecture(s). The default value for this is all architectures from 6.0 to 8.6 (Pascal to Ampere). Multiple architectures should be separated by semi-colons.

The C unit tests can then be run from the same build directory:

ctest

The Python library

From the top-level directory, run the following commands to install the Python package:

pip3 install .

The compiled library will be built as part of this step, so it does not need to be installed separately. If extra CMake arguments need to be specified, set the environment variable CMAKE_ARGS first, for example:

CMAKE_ARGS="-DCUDA_ARCH=8.0" pip3 install .

The Python unit tests can then be run using pytest, from the top-level directory:

pytest

Uninstalling

The Python package can be uninstalled using:

pip3 uninstall ska-sdp-func