DocumentCode
2953509
Title
Affect analysis of FFT algorithm length on traffic self-similarity in NOC
Author
Ming-Wei Qin ; Jian-Hao Hu ; Shang Ma
Author_Institution
Nat. Sci. & Technol. Key Lab. of Commun., Univ. of Electron. Sci. & Technol. of China, ChengDu, China
fYear
2013
fDate
17-19 Dec. 2013
Firstpage
149
Lastpage
152
Abstract
With network performance being highly dependent on the actual traffic, studies have shown that traffic is self-similar and long-range correlation in Network on Chip (NoC). The self-similarity of NoC traffic depends not only on the input sequence, but also changes with the processor algorithm on chip. In this paper, we improved firstly the existing method for generating sample traces of self-similar processes to suit Fast Fourier Transform (FFT) Algorithm. Then, Mainly studied the effects of FFT algorithm length for network traffic self-similarity in NoC by simulations. Experimental results show that the self-similarity of output sequence raised with the increasing of FFT length, and the output sequence is not self-similar when the length is long enough.
Keywords
fast Fourier transforms; network-on-chip; FFT algorithm length; NoC traffic; affect analysis; fast Fourier transform; network on chip; network performance; network traffic self-similarity; output sequence; processor algorithm; Algorithm design and analysis; Educational institutions; Integrated circuit modeling; Signal processing algorithms; System-on-chip; Very large scale integration; Wavelet transforms; FFT; Hurst exponent; Network on Chip; Self-similarity; Traffic;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2013 10th International Computer Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-2445-5
Type
conf
DOI
10.1109/ICCWAMTIP.2013.6716620
Filename
6716620
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