并行FFT在CUDA上的设计与实现

Xueqin Zhang, K. Shen, Cheng-Hai Xu, K. Wang
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引用次数: 4

摘要

快速傅里叶变换(FFT)算法是一种高度并行的分治算法,在图像处理和科学计算中有着重要的作用。在本文中,我们利用计算统一设备架构CUDA技术和现代图形处理单元(gpu)来实现更高的性能。我们主要从多线程并行性和内存层次两个方面对普通FFT算法进行优化。提出了数据量大时的并行优化策略,并预测了数据量进一步增加时可能出现的情况。从结果可以看出,并行FFT算法比普通FFT算法效率更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Implementation of Parallel FFT on CUDA
Fast Fourier Transform (FFT) algorithm has an important role in the image processing and scientific computing, and it's a highly parallel divide-and-conquer algorithm. In this paper, we exploited the Compute Unified Device Architecture CUDA technology and contemporary graphics processing units (GPUs) to achieve higher performance. We focused on two aspects to optimize the ordinary FFT algorithm, multi-threaded parallelism and memory hierarchy. We also proposed parallelism optimization strategies when the data volume occurs and predicted the possible situation when the amount of data increased further.it can be seen from the results that Parallel FFT algorithm is more efficient than the ordinary FFT algorithm.
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