Diagnosis of design-silicon timing mismatch with feature encoding and importance ranking - the methodology explained

Abstract

For sub-65 nm design, there can be many timing effects not explicitly and/or accurately modeled and simulated. For design-silicon timing convergence, this paper describes a novel path-based diagnosis approach that analyzes and ranks potential design related issues causing the unexpected timing effects. We explain in detail how a path can be encoded with a set of diverse "features" based on one's knowledge of the potential issues. We explain how these features can be interpreted differently in a data learning algorithm based on adjusting a so-called kernel function. Then, we explain how kernel-based data learning can be used to rank the importance of features such that a feature contributing the most to design-silicon timing mismatch is ranked the highest. We conclude the paper by showing an application result on an industrial ASIC design.