Scaling Parallel 3-D FFT with Non-Blocking MPI Collectives

This paper describes a new method for scalable high-performance parallel 3-D FFT. We use a 2-D decomposition of 3-D arrays to increase scaling to a large number of cores. In order to achieve high performance, we use non-blocking MPI all-to-all operations and exploit computation-communication overlap. We also auto-tune our 3-D FFT code efficiently in a large parameter space and cope with the complex trade-off in optimizing our code in various system environments. According to experimental results with up to 32,768 cores, our method computes parallel 3-D FFT faster than the FFTW library by up to 1.83×.