The analysis of static random access memory stability under the influence of statistical variability and bias temperature instability-induced ageing

Jie Ding; Asen Asenov

doi:10.1088/1361-6641/abcbd6

The analysis of static random access memory stability under the influence of statistical variability and bias temperature instability-induced ageing

Jie Ding^*, Asen Asenov

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

In this paper, the stability of static random access memory (SRAM) under the influence of statistical variability and bias temperature instability (BTI) induced ageing is investigated by statistical simulations. Effectively infinite and accurate compact models are successfully generated using ModelGen™ technology to prevent subsampling problem and ensure the statistical SRAM investigation, which successfully present device simulation results for circuits. The impact of transistor's statistical variability on the SRAM stability is evaluated by SRAM static noise margin (SNM) sensitivity test. Three BTI induced ageing patterns of the SRAM cell are analysed at different ageing levels. The distribution, increase and decrease percentage of SNM is calculated at statistical level to show the combined effects of transistors' variability with different ageing pattern.

Original language	English
Article number	025008
Journal	Semiconductor Science and Technology
Volume	36
Issue number	2
DOIs	https://doi.org/10.1088/1361-6641/abcbd6
Publication status	Published - Feb 2020
Externally published	Yes

Keywords

bias temperature instability
static noise margin
static random access memory
statistical variability

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10.1088/1361-6641/abcbd6

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abstract = "In this paper, the stability of static random access memory (SRAM) under the influence of statistical variability and bias temperature instability (BTI) induced ageing is investigated by statistical simulations. Effectively infinite and accurate compact models are successfully generated using ModelGen{\texttrademark} technology to prevent subsampling problem and ensure the statistical SRAM investigation, which successfully present device simulation results for circuits. The impact of transistor's statistical variability on the SRAM stability is evaluated by SRAM static noise margin (SNM) sensitivity test. Three BTI induced ageing patterns of the SRAM cell are analysed at different ageing levels. The distribution, increase and decrease percentage of SNM is calculated at statistical level to show the combined effects of transistors' variability with different ageing pattern.",

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N2 - In this paper, the stability of static random access memory (SRAM) under the influence of statistical variability and bias temperature instability (BTI) induced ageing is investigated by statistical simulations. Effectively infinite and accurate compact models are successfully generated using ModelGen™ technology to prevent subsampling problem and ensure the statistical SRAM investigation, which successfully present device simulation results for circuits. The impact of transistor's statistical variability on the SRAM stability is evaluated by SRAM static noise margin (SNM) sensitivity test. Three BTI induced ageing patterns of the SRAM cell are analysed at different ageing levels. The distribution, increase and decrease percentage of SNM is calculated at statistical level to show the combined effects of transistors' variability with different ageing pattern.

AB - In this paper, the stability of static random access memory (SRAM) under the influence of statistical variability and bias temperature instability (BTI) induced ageing is investigated by statistical simulations. Effectively infinite and accurate compact models are successfully generated using ModelGen™ technology to prevent subsampling problem and ensure the statistical SRAM investigation, which successfully present device simulation results for circuits. The impact of transistor's statistical variability on the SRAM stability is evaluated by SRAM static noise margin (SNM) sensitivity test. Three BTI induced ageing patterns of the SRAM cell are analysed at different ageing levels. The distribution, increase and decrease percentage of SNM is calculated at statistical level to show the combined effects of transistors' variability with different ageing pattern.

KW - bias temperature instability

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The analysis of static random access memory stability under the influence of statistical variability and bias temperature instability-induced ageing

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Keywords

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