Negative Bias Temperature Instability (NBTI) effect occurs in a PMOS transistor when turned ON leading to threshold voltage degradation. As sub-threshold leakage is significant in nanoscale CMOS circuits, input vector control can be employed wherein a Minimum Leakage Vector (MLV) is applied to the circuit during idle periods. In such a case, the ON PMOS transistors on the critical path are subject to NBTI stress for prolonged periods. Transistors can recover from stress when turned OFF. Based on this observation, we propose a vector cycling based leakage/NBTI co-optimization: a pair of MLVs are identified such that when applied alternately, on the critical path, PMOS transistors activated by one vector are turned OFF by the other vector. We employ Simulated Annealing (SA) for stochastic search of the first vector followed by back tracking to identify the second vector. Experimental results for a subset of ISCAS85 benchmarks implemented in 45 nm technology demonstrate the feasibility of vector cycling approach. When compared to leakage-only optimization, NBTI-only optimization, and co-optimization, on average, vector cycling yields 11, 3, and 6 percent NBTI improvements with 18, −9, and 4 percent leakage overheads respectively. The average area and dynamic power overheads are 13.78 and 0.15 percent respectively.

中文翻译：

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具有输入向量循环的组合电路中的门级 NBTI 和泄漏协同优化

PMOS 晶体管导通时会出现负偏置温度不稳定性 (NBTI) 效应，从而导致阈值电压下降。由于亚阈值泄漏在纳米级 CMOS 电路中很重要，因此可以采用输入矢量控制，其中在空闲期间将最小泄漏矢量 (MLV) 应用于电路。在这种情况下，关键路径上的 ON PMOS 晶体管会长时间承受 NBTI 应力。晶体管在关闭时可以从压力中恢复。基于这一观察，我们提出了基于矢量循环的泄漏/NBTI 协同优化：确定一对 MLV，这样当交替应用时，在关键路径上，由一个矢量激活的 PMOS 晶体管被另一个矢量关闭。我们采用模拟退火 (SA) 对第一个向量进行随机搜索，然后回溯以识别第二个向量。在 45 nm 技术中实施的 ISCAS85 基准测试子集的实验结果证明了矢量循环方法的可行性。与仅泄漏优化、仅 NBTI 优化和协同优化相比，向量循环平均可产生 11%、3% 和 6% 的 NBTI 改进，泄漏开销分别为 18%、-9% 和 4%。平均面积和动态功率开销分别为 13.78% 和 0.15%。矢量循环分别产生 11%、3% 和 6% 的 NBTI 改进，泄漏开销分别为 18%、-9% 和 4%。平均面积和动态功率开销分别为 13.78% 和 0.15%。矢量循环分别产生 11%、3% 和 6% 的 NBTI 改进，泄漏开销分别为 18%、-9% 和 4%。平均面积和动态功率开销分别为 13.78% 和 0.15%。