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[Keyword] macro model(2hit)

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  • A New LDMOS Transistor Macro-Modeling for Accurately Predicting Bias Dependence of Gate-Overlap Capacitance

    Takashi SAITO  Toshiki KANAMOTO  Saiko KOBAYASHI  Nobuhiko GOTO  Takao SATO  Hitoshi SUGIHARA  Hiroo MASUDA  

     
    PAPER-VLSI Design Technology and CAD

      Vol:
    E93-A No:9
      Page(s):
    1605-1611

    We have developed a macro model, which allows us to describe precise LDMOS DC/AC characteristics. Characterization of anomalous gate input capacitance is the key issue in the LDMOS model development. We have newly employed a T-type distributed RC scheme for gate overlapped LDMOS drift region. The bias dependent resistance and capacitance are modeled independently in Verilog-A as R-model and PMOS-capacitance. The dividing factor of the distributed R is introduced to reflect the shield effect of the gate overlap capacitance. Comparison between the new model and measurement results has proven that the developed macro model reproduces accurately not only the gate input capacitance, but also DC characteristics.

  • An Efficient Algorithm for RTL Power Macro-Modeling and Library Building

    Masaaki OHTSUKI  Masato KAWAI  Masahiro FUKUI  

     
    PAPER

      Vol:
    E92-C No:4
      Page(s):
    500-507

    Accompanying with the popularization of portable equipments, and the rapid growth of the size of the electric systems, efficient low power design methodologies have been highly required. To satisfy these requests, a high accurate and high efficient power analysis in higher abstraction level is very important. The design environment is composed by efficient algorithms of power modeling, power library building, and data extracting. Those components of the environment should be balanced for the total efficiency and accuracy. We have proposed a new efficient power modeling environment which uses a look-up table (LUT). It reduces the size of the LUT drastically, compared to conventional algorithms. It makes the power analysis and library building high efficient. The experimental results show that our approach reduces the computation time to build the library to one tenth while keeping the accuracy of the power analysis. The RMS error and the largest error has been less than 8.30%, 59.16%, respectively.