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Accurate Prediction of Random Telegraph Noise Effects in SRAMs and DRAMs

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4 Author(s)
Aadithya, K.V. ; Univ. of California, Berkeley, Berkeley, CA, USA ; Demir, A. ; Venugopalan, S. ; Roychowdhury, J.

With aggressive technology scaling and heightened variability, circuits such as SRAMs and DRAMs have become vulnerable to random telegraph noise (RTN). The bias dependence (i.e., non-stationarity), bi-directional coupling, and high inter-device variability of RTN present significant challenges to understanding its circuit-level effects. In this paper, we present two computer-aided design (CAD) tools, SAMURAI and MUSTARD, for accurately estimating the impact of non-stationary RTN on SRAMs and DRAMs. While traditional (stationary) analysis is often overly pessimistic (e.g., it overestimates RTN-induced SRAM failure rates), the predictions made by SAMURAI and MUSTARD are more reliable by virtue of non-stationary analysis.

Published in:

Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on  (Volume:32 ,  Issue: 1 )

Date of Publication:

Jan. 2013

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