Fin Field Effect Transistor (FinFET) technology has increasingly been adopted for use within integrated circuits thanks to its superior electrical integrity and scalability. However a steady increase in vulnerability of FinFET circuits to negative bias temperature instability (NBTI) has recently become one of the major lifetime reliability problems. In this paper we propose a simulation framework to address NBTI in combinational circuits implemented with 14-nm tri-gate FinFET predictive technology. Particle swarm optimization (PSO) algorithm is applied to construct an accurate long-term NBTI degradation model from cycle-by-cycle data history. The proposed simulation methodology provides accurate results with high efficacy in computation time compared to reference models. From the proposed framework the average delay degradation for all experimental circuits under normal operation after 10-year NBTI stress is approximately 6% yet temperature variation in the circuit strongly influences NBTI degradation.

For modern processors two reliability issues namely increased leakage power and soft error rate continue to intensify as device technologies scale down to nanometers. While many researchers have proposed methods to efficiently control leakage power by tuning body bias few recent works have considered the quantitative negative impact of this technique on circuit soft error vulnerability. In this paper we introduce a novel body bias based approach for reliability improvement that correlates leakage reduction and soft error immunity degradation. The experimental results show that the proposed technique provides satisfactory leakage reduction with confined soft error degradation in 32 nm high-k/metal gate benchmark circuits.