Does the metaprogramming element of FFTW work well, or does it boil down to "If X=2^4, Y=FWD, Z=X: build24FWDX()"?
FWIW, proper hygienic macros and scientific focused array types makes this sort of meta-programming optimization in Julia kinda fun.
Though just using type dispatching / multi-methods might be all that’s needed. It all makes me want to have a reason to write that kind of optimized code... For example if you can lift the size, variable, and variability into types you could match on your config roughly like: “fft(X :: Pwr2_64, Y :: FWD, Dir :: REV, Var :: BIDIR, Z) = 2^4-2^(log2(X))”.
And FWIW the author of FFTW is a big Julia contributor / package author nowadays. A long time ago (2014) he did write a Julia-based version of FFTW:
https://github.com/JuliaLang/julia/pull/6193#issuecomment-61...
This was back before Julia could do auto-SIMD optimizations, and it got quite close to FFTW without SIMD. He mentioned somewhere that modern Julia should be able to get very close to FFTW with SIMD, given that Julia now has better inlining heuristics, interprocedural optimizations, automatic SIMD, etc. (2014 was the stone age for Julia). If you read the rest of the thread, most of the discussion was about a standard library system so FFTW could be moved out. With Julia v1.0 FFTW is now in the standard library, which gives room for a pure Julia FFT to be standard. So this should get revived soon and we will have a beautiful generic FFTW algorithm. I can't wait :)
Holy shit! As a long time user of both, I'd never put two and two together before.
Also:
> With Julia v1.0 FFTW is now in the standard library
Did you mean "FFTW is no longer in the standard library"? Since it's ... well ... not (it's a separate package that you have to install).
so you can just Pkg.add it rather than having to Pkg.clone it from a special source.