PureFFT

An implementation of FFT-Algorithm for General Factorizations by Cooley-Tukey, purely in Julia, licensed permissively.
Contributions welcome.

Why?

I am working on some projects which will be using FFT internally, but which will not be able to use GPL licensed code. Most projects I am aware of use FFTW (dual licensed GPL + Commercial by MIT) or other GPL licensed implementations of FFT.

I wanted to learn how the Algorithm works, so I spend a few afternoons on understanding the literature about it. Then I tried implementing it from scratch.

Long term, I would like to make this a drop in replacement for other FFT Packages, therefore we might need to commmit to matching an existing API.

What?

This package provides:

• a $O(n^2)$ DFT implementation which works on arbitrary sized arrays
• a Type for holding a FFT-Plan (FFTPlan)
• a plan_fft function that plans the FFT for a known length
  • supporting Decimation-in-Frequency (method=:dif) and Decimation-in-Time (method=:dit)
  • supporting the Min-Radix planning style (rad=:min)
• a Cooley-Tukey FFT implementation for applying such plans to an array
• base-cases for arrays of sizes [1,2,4] to further improve execution speed

Additional Info

For the following highly composite numbers the execution time on my M1 MacBook Air is:

Size	Time	DFT-Time
1024	6.2e-4s	1.9e-2s
1680	9.4e-4s	5.3e-2s
2048	1.4e-3s	7.8e-2s
5040	3.3e-3s	4.8e-1s
27720	2.2e-2s	14.7s

TODO's

• Register as Julia Package
• Performance Benchmarking & Optimization
• Type Stability Checking
• Edge Case Hunting
• Max-Radix Plan not yet implemented
• Exhaustive Testing for Planning Method+Approach Combinations
• Write the one-stop shop fft function combining planning and execution.