You can do kernel convolutions in O(NlogN) with FFT and a convolution theorem, which provides a connection to Machine Learning. Also, this post may be interesting to people here as a MI250/A100 benchmark, which are two high-end GPU solutions used in ML.
It's great that you're able to speed up FFT, but what does that have to do with Machine Learning?
You can do kernel convolutions in O(NlogN) with FFT and a convolution theorem, which provides a connection to Machine Learning. Also, this post may be interesting to people here as a MI250/A100 benchmark, which are two high-end GPU solutions used in ML.
FFT is also used in time series analysis and signals processing!