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A Location Method for Reliability-Critical Paths Based on Monte Carlo Search Tree

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Machine Learning for Cyber Security (ML4CS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12488))

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Abstract

The development of nanoscale technology for integrated circuit chips highlights the reliability of circuit reliability. The path formed by the basic unit of the circuit has a significant influence on the overall reliability of the circuit. Therefore, it is necessary to quickly and effectively locate the path to understand the difference in reliability between logic circuits of different structures in time. Combined with the Monte Carlo tree search strategy and based on relaxation operations, this paper realizes the rapid location of sensitive paths in the combinational circuit while ensuring the accurate location of sensitive paths.

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Authors and Affiliations

  1. Zhejiang University of Technology, Hangzhou, 310023, China

    Ziwen Sun, Qiou Ji, Zecheng Wu & Aizhu Liu

Authors
  1. Ziwen Sun
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  2. Qiou Ji
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  3. Zecheng Wu
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  4. Aizhu Liu
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Corresponding author

Correspondence to Ziwen Sun .

Editor information

Editors and Affiliations

  1. Xidian University, Xi'an, China

    Xiaofeng Chen

  2. Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Michigan State University, East Lansing, MI, USA

    Qiben Yan

  4. Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science, Thuwal, Saudi Arabia

    Xiangliang Zhang

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Sun, Z., Ji, Q., Wu, Z., Liu, A. (2020). A Location Method for Reliability-Critical Paths Based on Monte Carlo Search Tree. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12488. Springer, Cham. https://doi.org/10.1007/978-3-030-62463-7_10

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  • DOI: https://doi.org/10.1007/978-3-030-62463-7_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62462-0

  • Online ISBN: 978-3-030-62463-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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