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release_notes.txt
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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.