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Modelling circuit performance variations due to statistical variability: Monte Carlo static timing analysis

Merrett, M. ; Asenov, P. ; Yangang Wang ; Zwolinski, M. ; Reid, D. ; Millar, C. ; Roy, S. ; Zhenyu Liu ; Furber, S. ; Asenov, A


The scaling of MOSFETs has improved performance and lowered the cost per function of CMOS integrated circuits and systems over the last 40 years, but devices are subject to increasing amounts of statistical variability within the deca-nano domain. The causes of these statistical variations and their effects on device performance have been extensively studied, but there have been few systematic studies of their impact on circuit performance. This paper describes a method for modelling the impact of random intra-die statistical variations on digital circuit timing and power consumption. The method allows the variation modelled by large-scale statistical transistor simulations to be propagated up the design flow to the circuit level, by making use of commercial STA and standard cell characterisation tools. The method provides circuit designers with the information required to analyse power, performance and yield trade-offs when fabricating a design, while removing the large levels of pessimism generated by traditional Corner Based Analysis.

IEEE Copyright