Publication:
Accurate prediction of random telegraph noise effects in srams and drams

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Aadithya, Karthik V.
Venugopalan, Sriramkumar
Roychowdhury, Jaijeet

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English

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Abstract

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.

Source:

IEEE Transactions On Computer-Aided Design of Integrated Circuits and Systems

Publisher:

IEEE-Inst Electrical Electronics Engineers Inc

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Subject

Computer science, hardware and architecture, Computer science, interdisciplinary applications, Engineering, electrical and electronic

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