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A Robust Test Architecture for Low-Power AI Accelerators
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Publication Year
2024-01-01
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Keyword
area overheadArtificial intelligence (AI)lowpower AI acceleratorpower consumptionsystolic arraytest coveragetoggle ratio
Mesh Keyword
Area overheadArtificial intelligenceData intensiveLow PowerLowpower artificial intelligence acceleratorPowerRobust testsTest architectureTest-coverageToggle ratio
All Science Classification Codes (ASJC)
SoftwareComputer Graphics and Computer-Aided DesignElectrical and Electronic Engineering
Abstract
With the rapid advancement of artificial intelligence (AI), there has been extensive research on AI accelerators to meet the demand for data-intensive analytics. Recently, low-power AI accelerators have been also developed to support battery-operated edge devices and minimize power consumption. However, traditional test architectures are insufficient for effectively testing such low-power AI accelerators. To address this issue, a robust test architecture for low-power AI accelerators has been proposed in this paper. The proposed test architecture employs a simple clock-gating technique in systolic array-based low-power AI accelerators and conducts testing through their functional paths. Accordingly, it can achieve 100 test coverage for both stuck-at and transition-delay faults with a minimal number of test patterns. Additionally, the proposed test architecture requires negligible area overhead since only one AND gate is implemented for the entire systolic array in low-power AI accelerators.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/34539
DOI
https://doi.org/10.1109/tcad.2024.3476464
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Article
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 Lee, Hayoung Image
Lee, Hayoung이하영
Department of Intelligence Semiconductor Engineering
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