International Journal of Information and Communication Sciences
Volume 5, Issue 1, March 2020, Pages: 1-7
Received: Jan. 31, 2020;
Accepted: Feb. 18, 2020;
Published: Feb. 26, 2020
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Bingfeng Qian, School of Mechanical Engineering, Donghua University, Shanghai, China; Machinery College, Shanghai Dianji University, Shanghai, China
Yize Sun, School of Mechanical Engineering, Donghua University, Shanghai, China
Qian Zhang, Department of Electronics and Electrical Engineering, Liverpool John Moores University, Liverpool, UK
Based on the theoretical research of a series of algorithms of adaptive beamforming and space-time adaptive processing, it is necessary to discuss the implementation of related algorithms on the machine hardware platform. Fast Fourier transform (FFT) is an essential process in this implementation. With the development of array antennas, the number of points to be calculated by the FFT has also increased significantly. Therefore, the ultra-large point FFT has become a key technology for current antenna signal processing. Most of the existing FFT algorithms are researched based on single-core processors, and there is very little literature on the research of super-large-point FFT algorithms suitable for Symmetric Multiprocessor (SMP). In this paper, through analyzing the characteristics of a symmetric multi-processor (SMP) parallel processing system, the very large FFT fast algorithm (VLFFT) is proposed. This algorithm significantly reduces the dependence on memory and improves the FFT's performance using the limited rules of the one-dimensional sequence split, changing the twiddle factor calculation method, and optimizing the data distribution and storage access. And the research's optimized very large FFT algorithms is also summarized in the paper. Experiment results show that the algorithm is suitable for the SMP platform and can effectively solve the problem of the very large FFT, which make single-core processors harder to realize.
Research on FFT Algorithm Use SMP System, International Journal of Information and Communication Sciences.
Vol. 5, No. 1,
2020, pp. 1-7.
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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