State Encoding based NBTI Optimization in Finite State Machines

Shilpa Pendyala and Srinivas Katkoori
University of South Florida Tampa


Several works in literature have proposed optimal state encoding techniques for delay, leakage, and dynamic power optimization. In this work, we propose for the first time, NBTI (Negative Bias Temperature Instability) optimization based on state code optimization. We propose a simulated annealing (SA) based state code assignment algorithm that results in minimization of NBTI degradation in the synthesized circuit. A PMOS transistor when switched ON for a long period of time, will lead to delay degradation due to NBTI. Therefore, in combinational circuits, an NBTI friendly input vector that stress least number of PMOS transistors on the critical path can be applied. For sequential circuits, the state code can significantly influence the ON/OFF mode of pMOS transistors in the controller implementation. Therefore, we propose to focus on state encoding. As the problem is computational intractable, we will focus on encoding states with high state probability. The following SA moves are employed: (a) code swap; and (b) code modification by flipping bits. Experiments with LGSYNTH93 benchmarks resulted in 18.6% improvement in NBTI degradation on average with area and power improvements of 5.5% and 4.6% respectively.