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A SEU Immune Flip-Flop with Low Overhead

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Machine Learning for Cyber Security (ML4CS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12487))

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Abstract

In nano-scale CMOS technologies, storage cells such as flip-flops are becoming increasingly sensitive to soft errors caused by harsh radiation effects. This paper proposes a radiation-hardened flip-flop with single event upset (SEU) immunity and low overhead. The flip-flop consists of a transfer unit, a storage unit and an output stage. The input signal propagates through transfer unit to the storage unit on the rising edge of the clock signal. The transfer unit uses the true single-phase clock (TSPC) scheme to simplify the clock distribution and reduce power consumption. The storage unit is composed of a radiation hardened memory (RHM) cell. Due to stacked PMOS structure and interlocked interconnect mechanism, SEU can be entirely tolerated. The C-element at output stage can filter any SEU occurred at storage unit. Compared with the existing radiation hardened flip-flops, the proposed flip-flop achieves 41.4% reduction in terms of delay on average, 82.6% reduction in terms of active power on average, 83.8% reduction in terms of power delay product on average and 39.7% reduction in terms of area on average.

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Authors and Affiliations

  1. Hefei University of Technology, Hefei, 230009, China

    Zhengfeng Huang, Xiandong Li, Shangjie Pan & Min Wang

  2. Anhui Polytechnic University, Wuhu, 241000, China

    Tianming Ni

Authors
  1. Zhengfeng Huang
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  2. Xiandong Li
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  3. Shangjie Pan
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  4. Min Wang
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  5. Tianming Ni
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Corresponding author

Correspondence to Tianming Ni .

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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Huang, Z., Li, X., Pan, S., Wang, M., Ni, T. (2020). A SEU Immune Flip-Flop with Low Overhead. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12487. Springer, Cham. https://doi.org/10.1007/978-3-030-62460-6_6

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  • DOI: https://doi.org/10.1007/978-3-030-62460-6_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62459-0

  • Online ISBN: 978-3-030-62460-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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