I need information regarding the FFT algorithm implemented in the CUDA SDK (FFT2D). I know the theory behind Fourier Transforms and DFT, but I can’t figure out what’s the purpose of the code (I do not need to modify it, I just need to understand it). Seems like data is padded to reach a 512-multiple (Cooley-Tuckey should be faster with that), but all the SpPreprocess and Modulate/Normalize things are just confusing me. No papers are attached to the SDK example, so can you please point me out on how to understand the algorithm thoroughly?
It may help, it’s still kinda confusing though.
I already saw the document but it doesn’t explain all the code, the problem is that after the FFT is performed a weird signal pre and post processing is executed simultaneously to the points multiplication. Why is it necessary? It uses weird twiddle factors too (like spreaded across the x values)
I simply cannot understand the code and I suppose a LOT of people can not too (I asked on many forums but they could not answer)
Well, I’m interested too. And I don’t really understand the point 2) of the 5th slide of the pdf. Do we fold the border pixel over the other border ?
To use it for images, we have to linearize it ? because the random data they use in the sample is 1D