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Dependability modeling and optimization of triple modular redundancy partitioning for SRAM-based FPGAs

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  • Hoque, Khaza Anuarul
  • Ait Mohamed, Otmane
  • Savaria, Yvon

Abstract

SRAM-based FPGAs are popular in the aerospace industry for their field programmability and low cost. However, they suffer from cosmic radiation-induced Single Event Upsets (SEUs). Triple Modular Redundancy (TMR) is a well-known technique to mitigate SEUs in FPGAs that is often used with another SEU mitigation technique known as configuration scrubbing. Traditional TMR provides protection against a single fault at a time, while partitioned TMR provides improved reliability and availability. In this paper, we present a methodology to analyze TMR partitioning at early design stage using probabilistic model checking. The proposed formal model can capture both single and multiple-cell upset scenarios, regardless of any assumption of equal partition sizes. Starting with a high-level description of a design, a Markov model is constructed from the Data Flow Graph (DFG) using a specified number of partitions, a component characterization library and a user defined scrub rate. Such a model and exhaustive analysis captures all the considered failures and repairs possible in the system within the radiation environment. Various reliability and availability properties are then verified automatically using the PRISM model checker exploring the relationship between the scrub frequency and the number of TMR partitions required to meet the design requirements. Also, the reported results show that based on a known voter failure rate, it is possible to find an optimal number of partitions at early design stages using our proposed method.

Suggested Citation

  • Hoque, Khaza Anuarul & Ait Mohamed, Otmane & Savaria, Yvon, 2019. "Dependability modeling and optimization of triple modular redundancy partitioning for SRAM-based FPGAs," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 107-119.
    • Handle: RePEc:eee:reensy:v:182:y:2019:i:c:p:107-119
    DOI: 10.1016/j.ress.2018.10.011
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    References listed on IDEAS

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    1. Prieto-Alfonso, H. & Del Peral, L. & Casolino, M. & Tsuno, K. & Ebisuzaki, T. & Rodríguez Frías, M.D., 2015. "Radiation Hardness Assurance for the JEM-EUSO Space Mission," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 137-145.
    2. Kretzschmar, U. & Gomez-Cornejo, J. & Astarloa, A. & Bidarte, U. & Ser, J. Del, 2016. "Synchronization of faulty processors in coarse-grained TMR protected partially reconfigurable FPGA designs," Reliability Engineering and System Safety, Elsevier, vol. 151(C), pages 1-9.
    3. Villalta, Igor & Bidarte, Unai & Gómez-Cornejo, Julen & Jiménez, Jaime & Lázaro, Jesús, 2018. "SEU emulation in industrial SoCs combining microprocessor and FPGA," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 53-63.
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    Cited by:

    1. Ramezani, Reza & Ghavidel, Abolfazl & Sedaghat, Yasser, 2021. "Exact and efficient reliability and performance optimization of synchronous task graphs," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    2. Wang, Xiaoyue & Zhao, Xian & Wang, Siqi & Sun, Leping, 2020. "Reliability and maintenance for performance-balanced systems operating in a shock environment," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    3. Yang, Shunkun & Shao, Qi & Bian, Chong, 2022. "Reliability analysis of ensemble fault tolerance for soft error mitigation against complex radiation effect," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    4. Granig, Wolfgang & Faller, Lisa-Marie & Hammerschmidt, Dirk & Zangl, Hubert, 2019. "Dependability considerations of redundant sensor systems," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    5. Cheng, Yao & Elsayed, E.A. & Chen, Xi, 2021. "Random Multi Hazard Resilience Modeling of Engineered Systems and Critical Infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    6. Jung, Sejin & Yoo, Junbeom & Lee, Young-Jun, 2020. "A practical application of NUREG/CR-6430 software safety hazard analysis to FPGA software," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    7. Ramezani, Reza & Clemente, Juan Antonio & Franco, Francisco J., 2020. "Analytical reliability estimation of SRAM-based FPGA designs against single-bit and multiple-cell upsets," Reliability Engineering and System Safety, Elsevier, vol. 202(C).

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