• DocumentCode
    3080352
  • Title

    Black-box leakage power modeling for cell library and SRAM compiler

  • Author

    Tseng, Chun-Kai ; Huang, Shi-Yu ; Weng, Chia-Chien ; Fang, Shan-Chien ; Chen, Ji-Jan

  • Author_Institution
    EE Dept., Nat. Tsing Hua Univ., Hsinchu, Taiwan
  • fYear
    2011
  • fDate
    14-18 March 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we present an automatic leakage power modeling method for standard cell library as well as SRAM compiler. For this problem, there are two major challenges - (1) the high sensitivity of leakage power to the temperature (e.g., the leakage power of an inverter can be different by 19.28X when temperature rises from 25°C to 100°C in 90nm technology), and (2) the large number of models to be built (e.g., there could be 80,835 SRAM macros supported by an SRAM compiler). Our method achieves high accuracy efficiently by two formula-based prediction techniques. First of all, we incorporate a quick segmented exponential interpolation scheme to take into account the effects of the temperature. Secondly, we use a MUX-oriented linear extrapolation scheme, which is so accurate that it allows us to build the leakage power models for all SRAM macros based on linear regression using only the simulation results of 9 small-sized SRAM macros. Experimental results show that this method is not only accurate but also highly efficient.
  • Keywords
    SRAM chips; extrapolation; macros; power aware computing; program compilers; MUX-oriented linear extrapolation scheme; SRAM compiler; SRAM macro; black-box leakage power modeling; cell library; exponential interpolation scheme; size 90 nm; Accuracy; Libraries; Random access memory; SPICE; Temperature distribution; Training; Leakage Power Estimation; Leakage Power Modeling; SRAM Compiler; Standard Cell Library;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design, Automation & Test in Europe Conference & Exhibition (DATE), 2011
  • Conference_Location
    Grenoble
  • ISSN
    1530-1591
  • Print_ISBN
    978-1-61284-208-0
  • Type

    conf

  • DOI
    10.1109/DATE.2011.5763105
  • Filename
    5763105