Mustard: a coupled, stochastic/deterministic, discrete/continuous technique for predicting the impact of random telegraph noise on SRAMS and DRAMS

Abstract

With aggressive technology scaling and heightened variability, SRAMs and DRAMs have become vulnerable to Random Telegraph Noise (RTN). The bias-dependent, random temporal nature of RTN presents significant challenges to understanding its effects on circuits. In this paper, we propose MUSTARD, a technique and tool for predicting the impact of RTN on SRAMs/DRAMs in the presence of variability. MUSTARD enables accurate, non-stationary, two-way-coupled, discrete stochastic RTN simulation seamlessly integrated with deterministic, continuous circuit simulation. Using MUSTARD, we are able to predict experimentally observed RTNinduced failures in SRAMs, and generate statistical characterisations of bit errors in SRAMs and DRAMs. We also present MUSTARD-generated results showing the effect of RTN on DRAM retention times. © 2011 ACM.