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Tsinghua Science and Technology 2022, 27(4): 729-740 https://doi.org/10.26599/TST.2020.9010032
Open Access | Issue | Published: 09 December 2021

Accurate Reliability Analysis Methods for Approximate Computing Circuits

Show Author's Information Zhen Wang,  Guofa Zhang,  Jing Ye( ),  Jianhui Jiang( ),  Fengyong Li,  Yong Wang
School of the Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China
Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
School of Software Engineering, Tongji University, Shanghai 200092, China
Keywords:
reliability, Approximate Computing Circuit (ACC), correlation coefficient, iterative Probabilistic Transfer Matrix (PTM)
Cite this article:
Wang Z, Zhang G, Ye J, et al. Accurate Reliability Analysis Methods for Approximate Computing Circuits. Tsinghua Science and Technology, 2022, 27(4): 729-740. https://doi.org/10.26599/TST.2020.9010032
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Abstract Full text About this article

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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Accurate Reliability Analysis Methods for Approximate Computing Circuits

Show Author's information Zhen Wang, Guofa Zhang, Jing Ye( ), Jianhui Jiang( ), Fengyong Li, Yong Wang
School of the Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China
Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
School of Software Engineering, Tongji University, Shanghai 200092, China

Abstract

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%.

Keywords: reliability, Approximate Computing Circuit (ACC), correlation coefficient, iterative Probabilistic Transfer Matrix (PTM)

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Publication history

Received: 29 July 2020
Accepted: 03 September 2020
Published: 09 December 2021
Issue date: August 2022

Copyright

© The author(s) 2022

Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (Nos. 61432017 and 61772327), the Natural Science Foundation of Shanghai (Nos. 20ZR1455900 and 20ZR1421600), and the Qi’anxin National Engineering Laboratory for Big Data Collaborative Security Technology Open Project (No. QAX-201803), and State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences (No. CARCHA202005).

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