Abstract
Aging is an important determinant for the reliability of circuit designs and has been addressed by a number of protection techniques based on static timing analysis (STA). The timing reported by STA, however, is often too optimistic without considering the functional behavior of the circuit. Furthermore, signal probability has also been found to be a significant factor in the aging effect. As such, we present in this paper a timing-critical path analysis that takes function and aging into account as well as signal probability. Functional timing analysis (FTA) eliminates the false paths and generates more accurate timing. Furthermore, machine learning can be used to build models for predicting the timing of each cell for various aging lifetimes and signal probabilities. Experimental results indicate that there can be a difference of up to 6% on path delay between STA and FTA. The path ranks also differ for most of the benchmark circuits after considering aging with signal probability, resulting in the delay differences of up to 6.12 %. In conclusion, it is necessary to consider function, aging, and signal probability simultaneously when analyzing timing-critical paths in a circuit design.
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