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

Placeholder

School / College / Institute

Program

KU-Authors

KU Authors

Co-Authors

Aadithya, Karthik V.
Venugopalan, Sriramkumar
Roychowdhury, Jaijeet

Publication Date

Language

Embargo Status

Journal Title

Journal ISSN

Volume Title

Alternative Title

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

Publisher

IEEE-Inst Electrical Electronics Engineers Inc

Subject

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

Citation

Has Part

Source

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

Book Series Title

Edition

DOI

10.1109/TCAD.2012.2212897

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

0

Views

0

Downloads

View PlumX Details