FFTW

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 468 articles , 1 standard article )

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  1. Bright, Curtis; Kotsireas, Ilias; Heinle, Albert; Ganesh, Vijay: Complex Golay pairs up to length 28: a search via computer algebra and programmatic SAT (2021)
  2. Anantharamu, Sreevatsa; Mahesh, Krishnan: Analysis of wall-pressure fluctuation sources from direct numerical simulation of turbulent channel flow (2020)
  3. Bright, Curtis; Kotsireas, Ilias; Ganesh, Vijay: Applying computer algebra systems with SAT solvers to the Williamson conjecture (2020)
  4. Cantisán, Julia; Coccolo, Mattia; Seoane, Jesús M.; Sanjuán, Miguel A. F.: Delay-induced resonance in the time-delayed Duffing oscillator (2020)
  5. Cayama, Jorge; Cuesta, Carlota M.; de la Hoz, Francisco: Numerical approximation of the fractional Laplacian on (\mathbbR) using orthogonal families (2020)
  6. Chillotti, Ilaria; Gama, Nicolas; Georgieva, Mariya; Izabachène, Malika: TFHE: fast fully homomorphic encryption over the torus (2020)
  7. Ernesti, Felix; Schneider, Matti; Böhlke, Thomas: Fast implicit solvers for phase-field fracture problems on heterogeneous microstructures (2020)
  8. Feng, Hongsong; Zhao, Shan: FFT-based high order central difference schemes for three-dimensional Poisson’s equation with various types of boundary conditions (2020)
  9. Héctor Andrade-Loarca, Gitta Kutyniok: tfShearlab: The TensorFlow Digital Shearlet Transform for Deep Learning (2020) arXiv
  10. Jose Manuel López; Daniel Feldmann; Markus Rampp; Alberto Vela-Martín; Liang Shie; Marc Avila: nsCouette - A high-performance code for direct numerical simulations of turbulent Taylor-Couette flow (2020) not zbMATH
  11. Khristenko, Ustim; Constantinescu, Andrei; Tallec, Patrick Le; Oden, J. Tinsley; Wohlmuth, Barbara: A statistical framework for generating microstructures of two-phase random materials: application to fatigue analysis (2020)
  12. Krause, Maximilian; Böhlke, Thomas: Maximum-entropy based estimates of stress and strain in thermoelastic random heterogeneous materials (2020)
  13. Lucas Frérot; Guillaume Anciaux; Valentine Rey; Son Pham-Ba; Jean-François Molinari: Tamaas: a library for elastic-plastic contact of periodic rough surfaces (2020) not zbMATH
  14. Pardeep Kaur, Arko Roy, Sandeep Gautam: FORTRESS: FORTRAN programs for solving coupled Gross-Pitaevskii equations for spin-orbit coupled spin-1 Bose-Einstein condensate (2020) arXiv
  15. Peter J. Christopher, Andrew Kadis, George S. D. Gordon, Timothy D. Wilkinson: HoloGen: An open source toolbox for high-speed hologram generation (2020) arXiv
  16. Reetz, Florian; Schneider, Tobias M.: Invariant states in inclined layer convection. I: Temporal transitions along dynamical connections between invariant states (2020)
  17. Schneider, Matti: A dynamical view of nonlinear conjugate gradient methods with applications to FFT-based computational micromechanics (2020)
  18. Wicht, Daniel; Schneider, Matti; Böhlke, Thomas: An efficient solution scheme for small-strain crystal-elasto-viscoplasticity in a dual framework (2020)
  19. Yan, Wen; Corona, Eduardo; Malhotra, Dhairya; Veerapaneni, Shravan; Shelley, Michael: A scalable computational platform for particulate Stokes suspensions (2020)
  20. Yazdanian, Hassan; Saturnino, Guilherme B.; Thielscher, Axel; Knudsen, Kim: Fast evaluation of the Biot-Savart integral using FFT for electrical conductivity imaging (2020)

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