Early prediction of NBTI effects using RTL source code analysis

Abstract

In present day technology, the design of reliable systems must factor in temporal degradation due to aging effects such as Negative Bias Temperature Instability (NBTI). In this paper, we present a methodology to estimate delay degradation early at the Register Transfer Level (RTL). We statically analyze the RTL source code to determine signal correlations. We then determine probability distributions of RTL signals formally by using probabilistic model checking. Finally, we propagate these signal probabilities through delay macromodels and estimate the delay degradation. We demonstrate our methodology on several benchmarks RTL designs. We estimate the degradation with <10% error and up to 18.2× speedup in runtime as compared to estimation using gate-level simulations.