• 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