Name | Modified | Size | Downloads / Week |
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gfft-0.1.zip | 2008-02-22 | 38.3 kB | |
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Release notes ------------------------------------------------------------------------------------------- Version 0.32 (2015-04-16) - Improved single- and multi-theaded performance (OpenMP) - CMake files contain support for GCC, Clang, Intel C++ and MSVC - Examples of compile-time computations of pi (metapi.cpp) and square root (metasqrt.cpp) - Fixed accuracy bug in single precision FFTs ------------------------------------------------------------------------------------------- Version 0.31 (2014-02-22) Accuracy and performance benchmarks added in the subfolder 'test' ------------------------------------------------------------------------------------------- Version 0.3 (2014-02-07) The project is back after 5 years break with a couple of new powerful features: - Out-of-place transforms - Complex transforms of any length N - Compile-time factorization of the input length N - Better accuracy due to compile-time computation of the roots-of-unity as rationals ------------------------------------------------------------------------------------------- Version 0.2 (2009-12-28) Completely redesigned release to make the usage even more simple and to implement many new features in the future. - New template class GenerateTransform to define a set of transforms. - New notation for different transform types taken from SPIRAL project. - The following transforms in-place are now implemented: DFT, IDFT, RDFT, IRDFT - Reordered template parameters for the transforms definitions, where most important parameters go first and less important parameters may be omitted using defaults. - Multithreaded parallelization using OpenMP standard - Bug fixes ------------------------------------------------------------------------------------------- Version 0.11 (2008-07-04) Bug-fixig release ------------------------------------------------------------------------------------------- Version 0.1 (2008-02-22) Initial release of GFFT with the following features: - Transforms in-place - Complex FFT of power-of-two length - Real-valued FFT of power-of-two length - High and cache-independent performance - No additional data is stored. - You can use all available RAM for your transform data - One-step transform. Many known FFT implementation perform to steps: initialization and transform. Initialization for a given length is usually computationally expensive, while transform is fast. GFFT needs only to create an object instance that includes FFT-algorithm, but no additional data or computation.