Efficient multilevel formal analysis and estimation of design vulnerability to Single Event Transients

The progressive shrinking of device size in advanced technologies leads to miniaturization and performance improvements. However, ultra-deep sub-micron technologies are more vulnerable to soft errors. Error analysis of a complex system with a sufficiently large sample of vulnerable nodes takes a large amount of time. In this paper we propose RASVAS, a hierarchical statistical method to model, analyze, and estimate the behavior of a system in the presence of Single Event Transients (SETs) modeled at different abstraction levels. Gate level propagation tables are developed to abstract SET propagation conditions and probabilities from gate level models. At RTL, these tables are utilized to model the underlying probabilistic behavior as Markov Decision Process (MDP) models. Experimental results demonstrate that RASVAS is orders of magnitude faster than contemporary techniques and also handle designs as large as 256-bit adders while maintaining accuracy.