Developer notes

  • Developers needing to update/regenerate documentation in general, including our readthedocs website, see docs/README. Developers changing MATLAB/octave interfaces or docs, also see matlab/README.

  • To update the version number, this needs to be done by hand in the following places:

    • CMakeLists.txt for cmake

    • docs/ for sphinx

    • python/finufft/ for the python pkg version

    • python/cufinufft/ for the GPU python pkg version

    • include/finufft/defs.h for the debug>0 output

    • matlab/Contents.m for the MATLAB/Octave help

    • CHANGELOG: don’t forget to describe the new features and changes, folding lines at 80 chars.

  • There are some sphinx tags in the source code, indicated by @ in comments. Please leave these alone since they are needed by the doc generation.

  • If you add a new option field (recall it must be plain C style only, no special types) to include/finufft_opts.h, don’t forget to add it to include/finufft.fh, include/finufft_mod.f90, matlab/, python/finufft/, and the Julia interface, as well a paragraph describing its use in the docs. Also to set its default value in src/finufft.cpp. You will then need to regenerate the docs as in docs/README.

  • For testing and performance measuring routines see test/README and perftest/README. We need more of the latter, eg, something making performance graphs that enable rapid eyeball comparison of various settings/machines.

  • Continuous Integration (CI). See files for this in .github/workflows/. It currently tests the default makefile settings in linux, and three other* files covering OSX and Windows (MinGW). CI does not test build the variant OMP=OFF. The dev should test these locally. Likewise, the Julia wrapper is separate and thus not tested in CI. We have added JenkinsFile for the GPU CI via python wrappers.

  • Installing MWrap. This is needed only for experts to rebuild the matlab/octave interfaces. MWrap is a very useful MEX interface generator by Dave Bindel, now maintained and expanded by Zydrunas Gimbutas. Make sure you have flex and bison installed to build it. As of FINUFFT v2.0 you will need a recent (>=0.33.10) version of MWrap. Make sure to override the location of MWrap by adding a line such as:

    MWRAP = your-path-to-mwrap-executable

    to your, and then you can use the make mex task.

  • The cufinufft Python wheels are generated using Docker based on the manylinux2014 image. For instructions, see tools/cufinufft/ These are binary wheels that are built using CUDA 11 (or optionally CUDA 12, but these are not distributed on PyPI) and bundled with the necessary libraries.

  • Testing cufinufft (for FI, mostly)

# to grab an interactive GPU shell -- here with 10 cores for building and a v100 for
# testing. You could just as easily try this on your workstation
srun -p gpu -C v100 -c 10 -n 1 --gpus=1 --pty bash
cd path/to/finufft

# get the local card to this machine's compute capability. If you know it you can obviously type it yourself
CUDAARCH=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader|head -n 1| sed 's/\.//')

# Load modules and build a venv. We typically recommend using venvs that fall back our our
# default packages with the python module (--system-site-packages)
module -q purge
module -q load gcc python cmake fftw cuda
python -m venv venv --system-site-packages
source venv/bin/activate
pip install --upgrade pip

# building. Feel free to tweak whatever
mkdir -p build && cd build
make -j 10

# for standard tests

# python install. Needs build from before since installer searches for in
# LD_LIBRARY_PATH (and default path)
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$PWD pip install -e ../python/cufinufft

# python tests. we have other GPU framework support, but you need to make sure they're
# installed (numba, pycuda, torch, cupy). This LD_LIBRARY_PATH may or may not be necessary,
# depending on if an RPATHing issue appears. Fix upstream at time of writing
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$PWD python -m pytest --framework=numba ../python/cufinufft