Research on FFT Algorithms for Peta-Scale Computing Environment

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In this research, we investigated an implementation of parallel fast Fourier transform (FFT) algorithm for peta-scale computing environment. Since the optimal cache block size may depend on the problem size, we proposed a method to determine the optimal cache block size that minimizes the number of cache misses. In addition, parallel FFTs require intensive all-to-all communication, which affects the performance of FFTs. An automatic tuning of all-to-all communication was also implemented. The performance results demonstrate that the proposed implementation of parallel FFTs with automatic performance tuning is efficient for improving the performance.