Runtime Leakage Minimization Through Probability-Aware Optimization

Runtime leakage current, defined as circuit leakage during normal operation (i.e., nonstandby mode), has become a major concern in very advanced technologies along with traditional standby mode leakage. In this paper, we propose a new leakage reduction method that specifically targets runtime leakage current. We first observe that the state probabilities of nodes in a circuit tend to be skewed, meaning that they have either high or low values. We then propose a method that exploits these skewed state probabilities by setting only those transistors to high-
$V_t$
(thick-oxide) that have a high likelihood of being off (on) and, hence, contributing significantly to the total runtime leakage. Accordingly, we also propose a library specifically tailored to the proposed approach, where
$V_t$
and
$T_ ox$
assignment with favorable tradeoffs under skewed input probabilities is provided. For further leakage reduction, we also introduce circuit resynthesis using pin reordering, pin rewiring, mapping, and decomposition. The optimization algorithm shows substantial leakage improvement over probability unaware optimization using a traditional standard cell library.