Test and Reliability Challenges for Approximate Circuitry

Polian, Ilia

doi:10.1109/les.2017.2754446

Cited by 6 publications

(4 citation statements)

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“…Studies focusing on the reliability of ACC are few. A number of scholars [22,23] have emphasized the necessity of reliability analysis for ACCs, but their research is not extensive. Reference [24] selected an error-tolerant application, i.e., H.264/AVC decoder, to evaluate fault criticality in different modules and in the same modules.…”

Section: Related Workmentioning

confidence: 99%

Accurate reliability analysis methods for approximate computing circuits

Wang

Zhang

et al. 2022

Tsinghua Sci. Technol.

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In recent years, Approximate Computing Circuits (ACCs) have been widely used in applications with intrinsic tolerance to errors. With the increased availability of approximate computing circuit approaches, reliability analysis methods for assessing their fault vulnerability have become highly necessary. In this study, two accurate reliability evaluation methods for approximate computing circuits are proposed. The reliability of approximate computing circuits is calculated on the basis of the iterative Probabilistic Transfer Matrix (PTM) model. During the calculation, the correlation coefficients are derived and combined to deal with the correlation problem caused by fanout reconvergence. The accuracy and scalability of the two methods are verified using three sets of approximate computing circuit instances and more circuits in EvoApprox8b, which is an approximate computing circuit open source library. Experimental results show that relative to the Monte Carlo simulation, the two methods achieve average error rates of 0.46% and 1.29% and time overheads of 0.002% and 0.1%. Different from the existing approaches to reliability estimation for approximate computing circuits based on the original PTM model, the proposed methods reduce the space overheads by nearly 50% and achieve time overheads of 1.78% and 2.19%.

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Section: Related Workmentioning

confidence: 99%

Accurate reliability analysis methods for approximate computing circuits

Wang

Zhang

et al. 2022

Tsinghua Sci. Technol.

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“…The threshold testing [122] was proposed in order to increase the production yield of conventional circuits (i.e., nonapproximate circuits). A similar approach was adopted by Sindia et al [123] to functionally classify conventional ICs [116].…”

Section: A Axa Testing Principlesmentioning

confidence: 99%

“…By solving the SAT problem, one can prove whether the input vector i exists or not. Both the mentioned techniques formally prove whether the vector i exists or not [116]. Concerning the full adder example, the vector i exists for five out of ten faults, classified as non-redundant according to WCE metric.…”

Section: B Sct-metric-aware Fault Classificationmentioning

confidence: 99%

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A Survey of Testing Techniques for Approximate Integrated Circuits

et al. 2020

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Approximate Computing (AxC) is increasingly emerging as a new design paradigm to produce more efficient computation systems by judiciously reducing the computation quality. In particular, AxC has been successfully applied to Integrated Circuits (ICs), in the last years. Hence, concerning the test of such new class of ICs, namely Approximate Integrated Circuits (AxICs), new challenges -as well as new opportunities -have emerged. In this survey, we provide a thorough analysis of issues related to test procedures for AxICs and review the state-of-the-art techniques to deal with them. We resort to an illustrative example having the twofold aim of: (i) guiding the reader through the AxIC testing challenges and (ii) illustrating the existing solutions to correctly overcome them, while suitably taking advantage of opportunities coming from approximation. We analyze experimentally the most recent testing techniques for AxICs and highlight their mature aspects, as well as their shortcomings. Experimental outcomes show that the testing process for AxIC is not completely mature. Indeed, only under specific conditions existing testing procedures achieve good results.

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