Performance analysis and autotuning setup of the cuFFT library
David Střelák, Jiří Filipovič · 2018
Fast Fourier transform (FFT) has many applications. It is often one of the most computationally demanding kernels, so a lot of attention has been invested into tuning its performance on various hardware devices. However, FFT libraries have usually many possible settings and it is not always easy to deduce which settings should be used for optimal performance. In practice, we can often slightly modify the FFT settings, for example, we can pad or crop input data. Surprisingly, a majority of state-of-the-art papers focus to answer the question how to implement FFT under given settings but do not pay much attention to the question which settings result in the fastest computation.