Abstract
The growing impact of process variations on circuit performance has become a major concern for deep-submicron integrated circuit design, resulting in numerous SSTA-algorithms. The acceptance of such algorithms in industry however will be dependent on modeling the real silicon behavior in SSTA. This includes that the statistical gate-delay models must consider arbitrary process variations and dependencies. In this paper, we introduce the innovative concept of Copulas to handle this topic. A complete Matlab based framework starting from process parameter statistics up to the computation of the statistical gate-delay distribution is presented. Experimental results demonstrate the importance of accounting realistic process variations.
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