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一种基于二叉胖树模型的并行FFT算法
引用本文:魏文红高大利. 一种基于二叉胖树模型的并行FFT算法[J]. 计算机应用, 2007, 27(4): 795-797
作者姓名:魏文红高大利
作者单位:华南理工大学,计算机科学与工程学院,广东,广州,510640;泉州师范学院,计算机系,福建,泉州,362000
摘    要:二叉胖树网络结构是一种易于实现蝶式计算的网络拓扑结构,基于这一特点,首先构造了一种二叉胖树的逻辑模型,并提出了一种基于该模型的并行快速傅立叶变换算法。该算法使得进程间有良好的负载平衡,相对于串行算法来说,大大降低了时间复杂度。在集群系统和MPI环境下,给出了该算法的实现及实验数据分析。

关 键 词:二叉胖树  蝶式计算  快速傅立叶变换  并行计算
文章编号:1001-9081(2007)04-0795-03
收稿时间:2006-10-12
修稿时间:2006-10-12

Parallel fast Fourier transform algorithm based on binary fat tree network
WEI Wen-hong,GAO Da-li. Parallel fast Fourier transform algorithm based on binary fat tree network[J]. Journal of Computer Applications, 2007, 27(4): 795-797
Authors:WEI Wen-hong  GAO Da-li
Affiliation:1. School of Computer Science and Engineering, South China University of Technology, Guangzhou Guangdong 510640, China; 2. Department of Computer, Quanzhou Normal College, Quanzhou Fujian 362000, China
Abstract:The binary fat tree is a network topology which is prone to accomplish butterfly computing. According to this feature, a logical model for binary fat tree was constructed at first, and then a parallel Fast Fourier Transform algorithm based on it was developed. In this algorithm, balance of load was achieved in the process, and time complexity was reduced compared with serial algorithm. At last the algorithm was implemented in cluster and MPI, and experimental data was analyzed.
Keywords:binary fat tree  butterfly computing  Fast Fourier Transform (FFT)  parallel computing
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