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Understanding SRAM Stability via Bifurcation Analysis: Analytical Models and Scaling Trends

Published: 29 August 2014 Publication History

Abstract

In the past decades, aggressive scaling of transistor feature size has been a primary force driving higher Static Random Access Memory (SRAM) integration density. Due to technology scaling, nanometer SRAM designs become increasingly vulnerable to stability challenges. The traditional way of analyzing stability is through the use of Static Noise Margins (SNMs). SNMs are not capable of capturing the key nonlinear dynamics associated with memory operations, leading to imprecise characterization of stability. This work rigorously develops dynamic stability concepts and, more importantly, captures them in physically based analytical models. By leveraging nonlinear stability theory, we develop analytical models that characterize the minimum required amplitude and duration of injected current noises that can flip the SRAM state. These models, which are parameterized in key design, technology, and operating condition parameters, provide important design insights and offer a basis for predicting scaling trends of SRAM dynamic stability.

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  • (2018)A continuation approach for computing parameter-dependent separatrices in SRAM cellsApplied Mathematical Modelling10.1016/j.apm.2018.07.00364(106-120)Online publication date: Dec-2018

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  1. Understanding SRAM Stability via Bifurcation Analysis: Analytical Models and Scaling Trends

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    cover image ACM Transactions on Design Automation of Electronic Systems
    ACM Transactions on Design Automation of Electronic Systems  Volume 19, Issue 4
    August 2014
    246 pages
    ISSN:1084-4309
    EISSN:1557-7309
    DOI:10.1145/2663459
    • Editor:
    • Naehyuck Chang
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 29 August 2014
    Accepted: 01 May 2014
    Revised: 01 May 2014
    Received: 01 October 2013
    Published in TODAES Volume 19, Issue 4

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    Author Tags

    1. Analytical model
    2. critical current
    3. critical time
    4. dynamic noise margin
    5. static noise margin
    6. static random access memory
    7. voltage transfer curves

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    • (2018)A continuation approach for computing parameter-dependent separatrices in SRAM cellsApplied Mathematical Modelling10.1016/j.apm.2018.07.00364(106-120)Online publication date: Dec-2018

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