Statistical logic cell delay analysis using a current-based model

  • Authors:
  • Hanif Fatemi;Shahin Nazarian;Massoud Pedram

  • Affiliations:
  • University of Southern California, Los Angeles, CA;University of Southern California, Los Angeles, CA;University of Southern California, Los Angeles, CA

  • Venue:
  • Proceedings of the 43rd annual Design Automation Conference
  • Year:
  • 2006

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Abstract

A statistical model for the purpose of logic cell timing analysis in the presence of process variations is presented. A new current-based cell delay model is utilized, which can accurately compute the output waveform for input waveforms of arbitrary shapes subjected to noise. The cell parasitic capacitances are pre-characterized by lookup tables to improve the accuracy. To capture the effect of process parameter variations on the cell behavior, the output voltage waveform of logic cells is modeled by a stochastic Markovian process in which the voltage value probability distribution at each time instance is computed from that of the previous time instance. Next the probability distribution of a%Vdd crossing time, i.e., the hitting time of the output voltage stochastic process is computed. Experimental results demonstrate the high accuracy of our cell delay model compared to Monte-Carlo-based SPICE simulations.