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
Link To Document :
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