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ABSTRACT

In this paper, we propose a novel methodology for statistical SRAM design and analysis. It relies on an efficient form of importance sampling, mixture importance sampling. The method is comprehensive, computationally efficient and the results are in excellent agreement with those obtained via standard Monte Carlo techniques. All this comes at significant gains in speed and accuracy, with speedup of more than 100X compared to regular Monte Carlo. To the best of our knowledge, this is the first time such a methodology is applied to the analysis of SRAM designs.

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INDEX TERMS

Primary Classification:
  B. Hardware
  B.7 INTEGRATED CIRCUITS
      B.7.2 Design Aids

General Terms:
Algorithms, Design, Performance, Reliability

Keywords:
SRAM, statistical performance analysis, yield prediction