Nima Sarajpoor
Nima Sarajpoor
Not sure if the following observation helps, but IIRC there was a [similar] discussion before around it and so I thought it might be a good idea to just think...
@seanlaw > I came across a more recent FFT implementation called [OTFFT](http://wwwa.pikara.ne.jp/okojisan/otfft-en/stockham2.html) that claims to be faster than FFTW and has a more generous MIT licene Cool! > Would you...
> Also: I have been trying `scipy.fft.rfft` / `scipy.fft.fft`. Also, as you mentioned before, I am using different number of workers, `1` vs `os.cpu_count()`. Haven't seen any improvement yet compared...
> Thanks @NimaSarajpoor. In case it matters (and if you're not already doing this), it would make sense to test window sizes and/or time series lengths in powers of `2`...
@seanlaw > @NimaSarajpoor I came across a more recent FFT implementation called [OTFFT](http://wwwa.pikara.ne.jp/okojisan/otfft-en/stockham2.html) that claims to be faster than FFTW and has a more generous MIT license. However, I tried...
@seanlaw > > It turns out that x will be output if we just avoid dividing it by n. > > Hmmm, I wonder why they performed the division?! Thanks...
For now, I did some enhancements on the new fft / ifft functions suggested in https://github.com/TDAmeritrade/stumpy/issues/938#issuecomment-1865067417. --- **Part (I):** I show the performance of four versions against the performance of...
> If I understand correctly, the stockham algorithm is NOT faster than `scipy.fft.convolve` (or they are about the same after some optimizations). Is that correct? And it also means that...
> we should consider implementing the [six step or eight step FFT algorithm](http://wwwa.pikara.ne.jp/okojisan/otfft-en/sixstepfft.html) next as it should have much better memory locailty and is therefore "optimized" I have implemented six-step-FFT....
According to [this Mathworks webpage](https://www.mathworks.com/discovery/matlab-multicore.html#:~:text=The%20built%2Din%20multithreading%20feature,mldivide%20%2C%20svd%20%2C%20and%20sort%20.), MATLAB is equipped with built-in multithreading. > The built-in multithreading feature in MATLAB automatically parallelizes computations using underlying libraries at runtime, resulting in significant performance...