Confronting the Variability Issues Affecting the Performance of Next-Generation SRAM Design to Optimize and Predict the Speed and Yield

Effectively confronting device and circuit parameter variations to maintain or improve the design of high performance and energy efficient systems while satisfying historical standards for reliability and lower costs is increasingly challenging with the scaling of technology. In this paper, we devel...

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Main Authors: Jeren Samandari-Rad, Matthew Guthaus, Richard Hughey
Format: Article
Language:English
Published: IEEE 2014-01-01
Series:IEEE Access
Online Access:https://ieeexplore.ieee.org/document/6815646/
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spelling doaj-a6f501c335134e8eaebf0ce03d46472e2021-03-29T19:29:55ZengIEEEIEEE Access2169-35362014-01-01257760110.1109/ACCESS.2014.23232336815646Confronting the Variability Issues Affecting the Performance of Next-Generation SRAM Design to Optimize and Predict the Speed and YieldJeren Samandari-Rad0Matthew Guthaus1Richard Hughey2Department of Electrical Engineering, University of California, Santa Cruz, CA, USADepartment of Computer Engineering, University of California, Santa Cruz, CA, USADepartment of Computer Engineering, University of California, Santa Cruz, CA, USAEffectively confronting device and circuit parameter variations to maintain or improve the design of high performance and energy efficient systems while satisfying historical standards for reliability and lower costs is increasingly challenging with the scaling of technology. In this paper, we develop methods for robust and resilient six-transistor-cell static random access memory (6T-SRAM) designs that mitigate the effects of device and circuit parameter variations. Our interdisciplinary effort involves: 1) using our own recently developed VAR-TX model [1] to illustrate the impact of interdie (also known as die-to-die, D2D) and intradie (also know as within-die, WID) process and operation variations - namely threshold voltage (Vth), gate length (L), and supply voltage (Vdd) - on future different 16-nm architectures and 2) using modified versions of other well-received models to illustrate the impact of variability due to temperature, negative bias temperature instability, aging, and so forth, on existing and next-generation technology nodes. Our goal in combining modeling techniques is to help minimize all major types of variability and to consequently predict and optimize speed and yield for the next generation 6T-SRAMs.https://ieeexplore.ieee.org/document/6815646/
collection DOAJ
language English
format Article
sources DOAJ
author Jeren Samandari-Rad
Matthew Guthaus
Richard Hughey
spellingShingle Jeren Samandari-Rad
Matthew Guthaus
Richard Hughey
Confronting the Variability Issues Affecting the Performance of Next-Generation SRAM Design to Optimize and Predict the Speed and Yield
IEEE Access
author_facet Jeren Samandari-Rad
Matthew Guthaus
Richard Hughey
author_sort Jeren Samandari-Rad
title Confronting the Variability Issues Affecting the Performance of Next-Generation SRAM Design to Optimize and Predict the Speed and Yield
title_short Confronting the Variability Issues Affecting the Performance of Next-Generation SRAM Design to Optimize and Predict the Speed and Yield
title_full Confronting the Variability Issues Affecting the Performance of Next-Generation SRAM Design to Optimize and Predict the Speed and Yield
title_fullStr Confronting the Variability Issues Affecting the Performance of Next-Generation SRAM Design to Optimize and Predict the Speed and Yield
title_full_unstemmed Confronting the Variability Issues Affecting the Performance of Next-Generation SRAM Design to Optimize and Predict the Speed and Yield
title_sort confronting the variability issues affecting the performance of next-generation sram design to optimize and predict the speed and yield
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2014-01-01
description Effectively confronting device and circuit parameter variations to maintain or improve the design of high performance and energy efficient systems while satisfying historical standards for reliability and lower costs is increasingly challenging with the scaling of technology. In this paper, we develop methods for robust and resilient six-transistor-cell static random access memory (6T-SRAM) designs that mitigate the effects of device and circuit parameter variations. Our interdisciplinary effort involves: 1) using our own recently developed VAR-TX model [1] to illustrate the impact of interdie (also known as die-to-die, D2D) and intradie (also know as within-die, WID) process and operation variations - namely threshold voltage (Vth), gate length (L), and supply voltage (Vdd) - on future different 16-nm architectures and 2) using modified versions of other well-received models to illustrate the impact of variability due to temperature, negative bias temperature instability, aging, and so forth, on existing and next-generation technology nodes. Our goal in combining modeling techniques is to help minimize all major types of variability and to consequently predict and optimize speed and yield for the next generation 6T-SRAMs.
url https://ieeexplore.ieee.org/document/6815646/
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