Incorporating Hot-Carrier Injection Effects Into Timing Analysis for Large Circuits

• Published in: IEEE transactions on very large scale integration (VLSI) systems Vol. 22; no. 12; pp. 2738 - 2751
• Main Authors: Jianxin Fang, Sapatnekar, Sachin S.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aging; Analytical models; carrier effects; circuit reliability; Computational modeling; Degradation; hot bias temperature instability (BTI); Integrated circuit modeling; Monte Carlo simulation; process variations (PVs); Timing; timing analysis; Transistors; Aging; hot bias temperature instability (BTI); process variations (PVs); timing analysis; carrier effects; circuit reliability
• ISSN: 1063-8210; 1557-9999
• DOI: 10.1109/TVLSI.2013.2296499

This paper focuses on hot-carrier effects in modern CMOS technologies and proposes a scalable method for analyzing circuit-level delay degradations in large digital circuits, using methods that take abstractions up from the transistor to the circuit level. We begin with an exposition of our approach for the nominal case. At the transistor level, a multimode energy-driven model for nanometer technologies is employed. At the logic cell level, a methodology that captures the aging of a device as a sum of device age gains per signal transition is described, and the age gain is characterized using SPICE simulation. At the circuit level, the cell-level characterizations are used in conjunction with probabilistic methods to perform fast degradation analysis. Next, we extend the nominal case analysis to include the effect of process variations. Finally, we show the composite effect of these approaches in the presence of other aging variations, notably bias temperature instability, and study the relative impact of each component of aging on the temporal trends of circuit delay degradations. The analysis approaches for nominal and variational cases are both validated by Monte Carlo simulation on various benchmark circuits, and are proved to be accurate, efficient, and scalable.