MUSTARD: a coupled, stochastic/deterministic, discrete/continuous technique for predicting the impact of random telegraph noise on SRAMs and DRAMs

Authors:
Karthik Aadithya;Sriramkumar Venogopalan;Alper Demir;Jaijeet Roychowdhury
Affiliations:
The University of California, Berkeley, CA;The University of California, Berkeley, CA;Koç University, Istanbul, Turkey;The University of California, Berkeley, CA
Venue:
Proceedings of the 48th Design Automation Conference
Year:
2011

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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 RTN-induced 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.