Predictive Testing for Aging in SRAMs and Mitigation

We develop a method to estimate lifetime performance, yield, and power for Static Random-Access Memories (SRAMs) that captures the combination of process variations and aging. Using this method, we design and validate predictive tests to detect future aging failures. We use the results of predictive tests to reconfigure dynamic voltage and frequency scaling (DVFS) to reduce aging failures at minimal energy and latency overheads.

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Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/itc51657.2024.00050
Citations
3
Primary Topic
Integrated Circuits and Semiconductor Failure Analysis
Type
article
Field-Weighted Citation Impact
0.63

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article

Predictive Testing for Aging in SRAMs and Mitigation

Yunkun Lin, Sandeep Gupta, Mingye Li
3 citations
Integrated Circuits and Semiconductor Failure Analysis
0.63
article

Predictive Testing for Aging in SRAMs and Mitigation

Yunkun Lin, Sandeep Gupta, Mingye Li
article en
3 citations

Abstract

We develop a method to estimate lifetime performance, yield, and power for Static Random-Access Memories (SRAMs) that captures the combination of process variations and aging. Using this method, we design and validate predictive tests to detect future aging failures. We use the results of predictive tests to reconfigure dynamic voltage and frequency scaling (DVFS) to reduce aging failures at minimal energy and latency overheads.

University of Southern California (US)
Semiconductor Research Corporation
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Openalex Percentile: Top 30%
Integrated Circuits and Semiconductor Failure Analysis
0.63
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