Title :
Parametric Yield Analysis and Optimization in Leakage Dominated Technologies
Author :
Agarwal, Kanak ; Rao, Rahul ; Sylvester, Dennis ; Brown, Richard
Author_Institution :
IBM Corp., Austin
fDate :
6/1/2007 12:00:00 AM
Abstract :
Parametric yield loss has become a serious concern in nanometer technologies. In this paper, we propose a methodology to estimate and optimize the parametric yield of a design in the presence of process variations. We discuss the impact of leakage on parametric yield given that leakage causes the parametric yield window to shrink by imposing a two-sided constraint in conjunction with performance targets on the yield window. We present a mathematical framework for yield estimation under process variation for a given power and frequency constraints. The model is validated against Monte Carlo SPICE simulations in a 90-nm CMOS process and is shown to have a typical error of less than 5%. We then demonstrate the importance of optimal supply and threshold voltage selection for yield maximization. Our results show that parametric yield is highly sensitive to supply voltage with only a 5% change in the supply voltage potentially leading to nearly 15% yield degradation. We also investigate the sensitivity of parametric yield to required frequency and power constraints. Finally, we apply the proposed framework to the problem of maximizing the shipping frequency in the presence of given yield and power constraints.
Keywords :
CMOS integrated circuits; Monte Carlo methods; SPICE; circuit optimisation; integrated circuit yield; CMOS process; Monte Carlo; SPICE simulations; frequency constraints; leakage dominated technology; nanometer technology; optimization; parametric yield analysis; power constraints; size 90 nm; voltage selection; yield estimation; Degradation; Design optimization; Energy consumption; Frequency estimation; Manufacturing; Monte Carlo methods; Power generation; Semiconductor device modeling; Threshold voltage; Yield estimation; Leakage; Yield estimation; optimal supply voltage; optimal threshold voltage; process variation; yield optimization;
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
DOI :
10.1109/TVLSI.2007.898625