TFT的高性能实现

Lingchuan Meng, Jeremy R. Johnson
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引用次数: 9

摘要

本文报道了截断傅立叶变换(TFT)的一种高性能实现。开发了一种通用的类似Cooley-Tukey的TFT算法,该算法允许实现自动适应内存层次结构。然后,该算法为较大的变换大小引入了一个小的松弛,以换取稍高的算法成本,从而改进了数据流,允许完全向量化和并行化。使用用于代码生成和调整的螺旋系统自动派生和调整实现。由此产生的任意大小的TFT库平滑了与2次幂模块化FFT实现相关的阶梯性能,同时保留了与最先进的FFT库相关的性能。即使在使用高性能FFT库的情况下,这也提供了显著的性能改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High performance implementation of the TFT
This paper reports on a high-performance implementation of the truncated Fourier transform (TFT). A general Cooley-Tukey like algorithm for the TFT is developed that allows the implementation to automatically adapt to the memory hierarchy. Then the algorithm introduces a small relaxation for larger transform sizes which trades off slightly higher arithmetic cost for improved data flow which allows full vectorization and parallelization. The implementation is automatically derived and tuned using the SPIRAL system for code generation and adaptation. The resulting arbitrary-size TFT library smooths out the staircase performance associated with power-of-two modular FFT implementations while retaining the performance associated with state-of-the-art FFT libraries. This provides significant performance improvement over approaches that pad to the next power of two even when using high-performance FFT libraries.
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