Library of Fast Fourier Transforms, Convolutions, and MPI Transposes built on FFTW3
Copyright © 2004-2024 by John C. Bowman, Malcolm Roberts, and Noel Murasko, University of Alberta http://fftwpp.sourceforge.net
FFTW++ is a C++ header/MPI transpose for Version 3 of the highly optimized FFTW Fourier Transform library. It provides a simple interface for 1D, 2D, and 3D complex-to-complex, real-to-complex, and complex-to-real Fast Fourier Transforms and convolutions. It takes care of the technical aspects of memory allocation, alignment, planning, wisdom, and communication on both serial and parallel (OpenMP/MPI) architectures. Wrappers for multiple 1D transforms are also provided. As with the FFTW3 library itself, both in-place and out-of-place transforms of arbitrary size are supported.
For reproducibility of Hybrid Dealiased Convolutions, see the test programs below.
Implicit dealiasing of standard and centered Hermitian convolutions is also implemented; in 2D and 3D implicit zero-padding substantially reduces memory usage and computation time. For more information, see
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Efficient Dealiased Convolutions without Padding, John C. Bowman and Malcolm Roberts. SIAM Journal on Scientific Computing, 33:1, 386-406 (2011): http://www.math.ualberta.ca/~bowman/publications/dealias.pdf
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Multithreaded implicitly dealiased convolutions, Malcolm Roberts and John C. Bowman. Journal of Computational Physics, 356, 98-114 (2018): http://www.math.ualberta.ca/~bowman/publications/dealias2.pdf
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Hybrid Dealiasing of Complex Convolutions, Noel Murasko and John C. Bowman.SIAM Journal on Scientific Computing (2024), in press: arXiv:2303.17510
Convenient optional shift routines that place the Fourier origin in the logical center of the domain are provided for centered complex-to-real transforms in 2D and 3D; see fftw++.h for details.
FFTW++ supports multithreaded transforms and convolutions. The global variable fftw::maxthreads specifies the maximum number of threads to use. The constructors invoke a short timing test to check that using multiple threads is actually beneficial for the given problem size. Multithreading requires linking with a multithreaded FFTW implementation and can be disabled by adding -DFFTWPP_SINGLE_THREAD to CFLAGS.
FFTW++ can also exploit the high-performance Array class available here (version 1.58 or higher), designed for scientific computing. The arrays in that package do memory bounds checking in debugging mode, but can be optimized by specifying the -DNDEBUG compilation option (1D arrays optimize completely to pointer operations).
Detailed documentation is provided before each class in the fftw++.h header file. The included examples illustrate how easy it is to use FFTW in C++ with the FFTW++ header class. Use of the Array class is optional, but encouraged. If for some reason the Array class is not used, memory should be allocated with ComplexAlign (or doubleAlign) to ensure that the data is optimally aligned to sizeof(Complex), to enable the SIMD extensions. The optional alignment check in fftw++.h can be disabled with the -DNO_CHECK_ALIGN compiler option.
The following programs are provided in the examples directory:
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1D examples using ComplexAlign allocator:
example0.ccexample0r.cc
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1D examples using Array class:
example1.ccexample1r.cc
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2D examples using Array class:
example2.ccexample2r.cc
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3D examples using Array class:
example3.ccexample3r.cc
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Examples of hybrid dealiased convolutions on complex data in 1, 2, and 3 dimensions:
exampleconv.ccexampleconv2.ccexampleconv3.cc
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Examples of hybrid dealiased convolutions on complex Hermitian-symmetric centered data in 1, 2, and 3 dimensions:
exampleconvh.ccexampleconvh2.ccexampleconvh3.cc
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Examples of hybrid dealiased convolutions on real data in 1, 2, and 3 dimensions:
exampleconvr.ccexampleconvr2.ccexampleconvr3.cc
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Local transpose (in-place or out-of-place):
exampletranspose.cc
More general types of convolutions (for example, autoconvolutions) can be performed by defining a custom multiplier function.
Wrappers for the convolution routines are available for C, Fortran, and Python. Examples are given in the wrappers/ directory. The C wrapper may be found in cfftw++.h and cfftw++.cc, the Fortran wrapper in fftwpp.f90, and the Python wrapper in fftwpp.py. A unit-testing script, test.py, is also available. Results for the given input data are checked with a simple hash.
Compilation uses the environment variables CPLUS_INCLUDE_PATH to tell the compiler where to find fftw3.h, and FORTRAN_INCLUDE_PATH to indicate to the compiler the location of fftw3.f03 from FFTW.
In the wrappers directory are examples of calling multi-threaded 1D, 2D, and 3D complex or Hermitian-symmetric convolutions from Python: pexample.py
C:
cexample.c
Fortan 90:
fexample.f90
OpenMP/MPI versions of the convolution routines in 2 and 3 dimensions are available in the mpi/ directory. Parallelization is accomplished using the adaptive hybrid OpenMP/MPI transpose routine described in
- Adaptive Matrix Transpose Algorithms for Distributed Multicore Processors, John C. Bowman and Malcolm Roberts. Interdisciplinary Topics in Applied Mathematics, Modeling and Computational Science, Springer Proceedings in Mathematics & Statistics 117, 97-103 (2015): http://www.math.ualberta.ca/~bowman/publications/transpose.pdf
Either a 1D ("slab") and 2D ("pencil") data decomposition is used for the three-dimensional convolutions, depending on the number of processors.
hybridconv2.cc and hybridconv3.cc demonstrate two- and three-dimensional complex convolutions.
hybridconvh2.cc and hybridconvh3.cc demonstrate two- and three-dimensional Hermitian-symmetric centered convolutions.
fft2.cc and fft2r.cc demonstrate two-dimensional MPI/OpenMP FFTs using a 1D data decomposition, for complex and real data, respectively.
fft3.cc and fft3r.cc demonstrate three-dimensional MPI/OpenMP FFTs for complex and real data, respectively.
timing.py is a script which performs timing tests for MPI-based convolutions.
The directory mpi/explicit is used for comparing our adaptive distributed transpose against FFTW's parallel MPI transpose.
The following programs are provided in tests/, along with various timing and error analysis scripts. Asymptote scripts are provided for visualizing the output. Passing the argument -h to each of these programs outputs usage information.
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1D complex convolution test:
hybridconv -
1D Hermitian convolution test:
hybridconvh -
1D real convolution test:
hybridconvr -
2D complex convolution test:
hybridconv2 -
2D Hermitian convolution test:
hybridconvh2 -
2D real convolution test:
hybridconvr2 -
3D complex convolution test:
hybridconv3 -
3D Hermitian convolution test:
hybridconvh3 -
1D FFT:
fft1 -
1D real FFT:
fft1r -
1D multiple FFT:
mfft1 -
1D multiple real FFT:
mfft1r -
2D FFT:
fft2 -
2D real FFT:
fft2r -
3D FFT:
fft3 -
3D real FFT:
fft3r
To compile from Git developmental source code:
git clone https://github.com/dealias/fftwpp
All source files in the FFTW++ project, unless explicitly noted otherwise, are released under version 3 (or later) of the GNU Lesser General Public License (see the files LICENSE.LESSER and LICENSE in the top-level source directory).
This program is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License along with this program; if not, write to the Free Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.