Towards a performance-portable FFT library for heterogeneous computing
Carlo del Mundo, Wu-chun Feng · 2014
The fast Fourier transform (FFT), a spectral method that computes the discrete Fourier transform and its inverse, pervades many applications in digital signal processing, such as imaging, tomography, and software-defined radio. Its importance has caused the research community to expend significant resources to accelerate the FFT, of which FFTW is the most prominent example. With the emergence of the graphics processing unit (GPU) as a massively parallel computing device for high performance, we seek to identify architecture-aware optimizations across two different generations of high-end AMD and NVIDIA GPUs, namely the AMD Radeon HD 6970 and HD 7970 and the NVIDIA Tesla C2075 and K20c, respectively, to accelerate FFT performance.