FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST). We believe that FFTW, which is free software, should become the FFT library of choice for most applications. The latest official release of FFTW is version 3.3.3, available from our download page. Version 3.3 introduced support for the AVX x86 extensions, a distributed-memory implementation on top of MPI, and a Fortran 2003 API. Version 3.3.1 introduced support for the ARM Neon extensions.

References in zbMATH (referenced in 410 articles , 1 standard article )

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  1. Bright, Curtis; Kotsireas, Ilias; Ganesh, Vijay: The SAT+CAS paradigm and the Williamson conjecture (2019)
  2. Corsaro, Stefania; Kyriakou, Ioannis; Marazzina, Daniele; Marino, Zelda: A general framework for pricing Asian options under stochastic volatility on parallel architectures (2019)
  3. Dyachenko, Sergey A.: On the dynamics of a free surface of an ideal fluid in a bounded domain in the presence of surface tension (2019)
  4. Eric W. Koch, Ryan D. Boyden, Blakesley Burkhart, Adam Ginsburg, Jason L. Loeppky, Stella S.R. Offner: TurbuStat: Turbulence Statistics in Python (2019) arXiv
  5. Gadioli, Davide; Vitali, Emanuele; Palermo, Gianluca; Silvano, Cristina: mARGOt: a dynamic autotuning framework for self-aware approximate computing (2019)
  6. Green, Kevin R.; Bohn, Tanner A.; Spiteri, Raymond J.: Direct function evaluation versus lookup tables: when to use which? (2019)
  7. Lambers, James V.; Sumner, Amber C.: Explorations in numerical analysis (2019)
  8. Mang, Andreas; Gholami, Amir; Davatzikos, Christos; Biros, George: CLAIRE: a distributed-memory solver for constrained large deformation diffeomorphic image registration (2019)
  9. Matteo Ravasi, Ivan Vasconcelos: PyLops - A Linear-Operator Python Library for large scale optimization (2019) arXiv
  10. Neumüller, Martin; Smears, Iain: Time-parallel iterative solvers for parabolic evolution equations (2019)
  11. Yazdanbakhsh, Omolbanin; Dick, Scott: FANCFIS: fast adaptive neuro-complex fuzzy inference system (2019)
  12. Ammon, Martin; Baggioli, Matteo; Jiménez-Alba, Amadeo; Moeckel, Sebastian: A smeared quantum phase transition in disordered holography (2018)
  13. Arduino, Alessandro; Bottauscio, Oriano; Chiampi, Mario; Zilberti, Luca: Magnetic resonance-based imaging of human electric properties with phaseless contrast source inversion (2018)
  14. Ashwin Vishnu Mohanan, Cyrille Bonamy, Pierre Augier: FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries (2018) arXiv
  15. Bali, Gunnar S.; Bruns, Peter C.; Castagnini, Luca; Diehl, Markus; Gaunt, Jonathan R.; Gläßle, Benjamin; Schäfer, Andreas; Sternbeck, André; Zimmermann, Christian: Two-current correlations in the pion on the lattice (2018)
  16. Beaudoin, Anthony; Huberson, Serge; de Dreuzy, Jean-Raynald: Adapting particle methods to model the dynamics of concentration gradients and chemical reactivity under advective diffusive transport conditions (2018)
  17. Biscarri, William; Zhao, Sihai Dave; Brunner, Robert J.: A simple and fast method for computing the Poisson binomial distribution function (2018)
  18. Bowman, John C.; Ghoggali, Zayd: The partial fast Fourier transform (2018)
  19. Cifani, P.; Kuerten, J. G. M.; Geurts, B. J.: Highly scalable DNS solver for turbulent bubble-laden channel flow (2018)
  20. Demidov, S. V.; Farkhtdinov, B. R.: Numerical study of multiparticle scattering in (\lambda\phi^4) theory (2018)

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