CUDA convolutionFFT2D example - I can't understand it

I studied the Cooley Tukey algorithm and I understood it. I got everything in the CUDA convolutionFFT2D example till these kernels:

spProcess2D calls -> spProcess2D_kernel which calls a lot of -> spPostprocessC2C, mulAndScale and spPreprocessC2C

Here's the complete code: http://nopaste.info/30c13e44fe.html (convolutionFFT2D.cu, here is the spProcess2D function) http://nopaste.info/78d22afac2.html (convolutionFFT2D.cuh, here are the other f开发者_运维百科unctions)

I already read all the nvidia sdk papers but I can't still figure out what these function do (they use twiddles, but nothing seems like a Cooley Tukey algorithm there)

Please help me if you can, or at least point me out where to solve my problem

Update: I found this link: http://cnx.org/content/m16336/latest/#uid38 Maybe these functions are performing a breadth-first algorithm? I still can't say that but the shape seems the same

It looks like the algorithm is doing something similar to the algorithm mentioned here. The preprocess step looks to be re-ordering the Real input of size N (after padding) to complex input of size N/2. The postprocess step is re-ordering the data to get back the FFT of the original input array.

spPostprocessC2C looks like a single FFT butterfly. The complexity in the calling routines just comes from fitting the FFT algorithm into a SIMT model for CUDA.

Perhaps if you explained what it is that you are trying to achieve (beyond just understanding how this particular FFT implementation works) then you might get some more specific answers.