Monte Carlo Static Timing Analysis with statistical sampling

• Published in: Microelectronics and reliability Vol. 54; no. 2; pp. 464 - 474
• Main Authors: Merrett, Michael, Zwolinski, Mark
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.02.2014; Elsevier
• Subjects: Applied sciences; Circuit properties; Computer simulation; Design. Technologies. Operation analysis. Testing; Devices; Digital circuits; Electric, optical and optoelectronic circuits; Electronic circuits; Electronics; Exact sciences and technology; Integrated circuits; Mathematical models; Monte Carlo methods; MOSFETs; Sampling; Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices; Static timing analysis; Transistors; Performance evaluation; MOS technology; Die; Monte Carlo method; MOSFET; Computational complexity; Modeling; Statistical method; Complementary MOS technology; Digital circuit; SPICE; Numerical simulation; Large scale; Sampling
• ISSN: 0026-2714; 1872-941X
• DOI: 10.1016/j.microrel.2013.10.016

•Extension of previously described Monte Carlo Static Timing Analysis.•We show how to reduce the number of samples needed to evaluate extreme behavior.•We demonstrate accuracy close to full Monte Carlo SPICE.•We demonstrate a speed close to Statistical Static Timing Analysis. With aggressive scaling of CMOS technologies, MOSFET devices are subject to increasing amounts of independent local statistical variability. The causes of these statistical variations and their effects on device performance have been extensively studied, but their impact on circuit performance is still difficult to predict. This paper proposes a method for modeling the impact of random intra-die statistical variations on digital circuit timing. The method allows the variation modeled by large-scale statistical transistor simulations to be propagated up the design flow to the circuit level, by making use of commercial STA and standard cell characterization tools. By using statistical sampling techniques, we achieve close to the accuracy of full SPICE simulation, but with a computational effort similar to that of Statistical Static Timing Analysis, while removing some of the inaccurate assumptions of Statistical Static Timing Analysis.