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More about FFT/DFT

The Fast Fourier Transform (FFT) can be used to perform:

Often, FFT is the most efficient way to perform each of these algorithms.

About KFR DFT implementation

The KFR implementation of the FFT:

  • is fully optimized for X86, X86-64, ARM and AARCH64 (ARM64) processors
  • uses vector intrinsics (if available for the cpu)
  • supports both single- and double-precision
  • supports in-place processing
  • supports multidimensional FFT
  • can cache internal data between calls to speed up plan creation
  • can do forward and inverse FFT without the need to create two plans
  • can be used for complex-to-complex, real-to-complex and complex-to-real transforms
  • doesn’t require measuring FFT performance at runtime to find an optimal configuration
  • has special implementations for FFT sizes up to 1024
  • has no external dependencies
  • is thread-safe, with no global data
  • is written in modern C++17
  • is open source (GPL v2+ license, commercial license is availalble for closed source projects, see )