Test and Reliability in Approximate Computing

Anghel, Lorena; Benabdenbi, Mounir; Bosio, Alberto; Traiola, Marcello; Vatajelu, Elena Ioana

doi:10.1007/s10836-018-5734-9

Cited by 23 publications

(6 citation statements)

References 35 publications

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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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“…In fact, the normal lifetime of miniaturized ICs is more and more reduced [30]. Approximate computing aims at transforming this problem into an opportunity [3]. The basic idea is to "embrace" errors as an intrinsic property of ICs and systematically design optimized approximate circuits functioning regardless of errors.…”

Section: Towards Approximate-computing-based Reliable Hardwarementioning

confidence: 99%

Test and Reliability of Approximate Hardware

Traiola

Deveautour

Bosio

et al. 2022

Approximate Computing

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…These circuits are referred to as Approximate Integrated Circuits (AxICs). Since approximating circuits alters their functional behavior, techniques to test them must be revisited [49,50,39,38,37,2,36,40,41,42,4]. As a matter of fact, extending the basic testing concepts to AxICs is not straightforward.…”

Section: Approximate Integrated Circuits Testing Phasementioning

confidence: 99%

Design, Verification, Test, and In-Field Implications of Approximate Digital Integrated Circuits

Bosio

Carlo

Girard

et al. 2022

Approximate Computing Techniques

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Today, the concept of approximation in computing is becoming more and more a "hot topic" to investigate how computing systems can be more energyefficient, faster, and less complex. Intuitively, instead of performing exact computations and, consequently, requiring a high amount of resources, Approximate Computing aims at selectively relaxing the specifications, trading accuracy off for efficiency. While Approximate Computing allows many improvements when looking at systems' performance, energy efficiency and complexity, it poses significant challenges regarding the design, the verification, the test and the in-field reliability of Approximate Digital Integrated Circuits. This chapter covers these aspects, leveraging the authors' experience in the field to present state-of-the-art solutions to apply during the different development phases of an Approximate Computing system.

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Test and Reliability in Approximate Computing

Cited by 23 publications

References 35 publications

Accurate reliability analysis methods for approximate computing circuits

Accurate reliability analysis methods for approximate computing circuits

Test and Reliability of Approximate Hardware

Design, Verification, Test, and In-Field Implications of Approximate Digital Integrated Circuits

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