|Scalability Issues in FFT Computation
|Year of Publication
|Ayala, A., S. Tomov, M. Stoyanov, and J. Dongarra
|International Conference on Parallel Computing Technologies
|Hybrid systems, Parallel FFT, scalability
The fast Fourier transform (FFT), is one the most important tools in mathematics, and it is widely required by several applications of science and engineering. State-of-the-art parallel implementations of the FFT algorithm, based on Cooley-Tukey developments, are known to be communication-bound, which causes critical issues when scaling the computational and architectural capabilities. In this paper, we study the main performance bottleneck of FFT computations on hybrid CPU and GPU systems at large-scale. We provide numerical simulations and potential acceleration techniques that can be easily integrated into FFT distributed libraries. We present different experiments on performance scalability and runtime analysis on the world’s most powerful supercomputers today: Summit, using up to 6,144 NVIDIA V100 GPUs, and Fugaku, using more than one million Fujitsu A64FX cores.
Scalability Issues in FFT Computation
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