Principal author Alex H. Barnett, main co-developers Jeremy F. Magland, Ludvig af Klinteberg, Yu-hsuan "Melody" Shih, Libin Lu, Joakim Andén, and Robert Blackwell; see docs/ackn.rst for full list of contributors. ​

This is a lightweight CPU library to compute the three standard types of nonuniform FFT to a specified precision, in one, two, or three dimensions. It is written in C++ with interfaces to C, Fortran, MATLAB/octave, Python, and (in a separate repository) Julia. It now also integrates the GPU CUDA library cuFINUFFT (which currently does all but type 3).

Please see the online documentation which can also be downloaded as a PDF manual. You will also want to see CPU example codes in the directories examples, test, fortran, matlab/test, matlab/examples, python/finufft/test, etc, and GPU examples in examples/cuda, test/cuda, etc

If you cannot build via cMake, try the old makefile. Python users try pip install finufft. See the docs for details. See our GitHub Issues for tips.

If you prefer to read text files, the source to generate the above documentation is in human-readable (mostly .rst) files as follows:

• docs/install.rst : installation and compilation instructions
• docs/install_gpu.rst : installation and compilation for GPU (CUDA)
• docs/dirs.rst : explanation of directories and files in the package
• docs/math.rst : mathematical definitions
• docs/cex.rst : example usage from C++/C
• docs/c.rst : documentation of C++/C function API
• docs/c_gpu.rst : documentation of C++/C function API for GPU library
• docs/opts.rst : optional parameters
• docs/error.rst : error codes
• docs/trouble.rst : troubleshooting advice
• docs/tut.rst and docs/tutorial/* : tutorial application examples
• docs/fortran.rst : usage examples from Fortran, documentation of interface
• docs/matlab.rst and docs/matlabhelp.raw : using the MATLAB/Octave interface
• docs/python.rst and python/*/_interfaces.py : using the Python interface
• docs/python_gpu.rst : Python interface to GPU library
• docs/julia.rst : options for Julia users
• docs/devnotes.rst: notes/guide for developers
• docs/related.rst : other recommended NUFFT packages
• docs/users.rst : some known users of FINUFFT, dependent packages
• docs/ackn.rst : authors and acknowledgments
• docs/refs.rst : journal article references (both ours and others)

If you find (cu)FINUFFT useful in your work, please cite this repository and the following. For FINUFFT (CPU library):

A parallel non-uniform fast Fourier transform library based on an ``exponential of semicircle'' kernel. A. H. Barnett, J. F. Magland, and L. af Klinteberg. SIAM J. Sci. Comput. 41(5), C479-C504 (2019).

For cuFINUFFT (GPU library):

cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTs, Yu-hsuan Shih, Garrett Wright, Joakim Andén, Johannes Blaschke, Alex H. Barnett, PDSEC2021 workshop of the IPDPS2021 conference. https://arxiv.org/abs/2102.08463