软误差免疫电路设计的多目标优化框架

2019 19th European Conference on Radiation and Its Effects on Components and Systems (RADECS) Pub Date : 2019-09-01 DOI:10.1109/radecs47380.2019.9745725

Yan Li, Jun Han, Yu-Jiao Han, Xiao-yang Zeng, Xiaoyang Zeng

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引用次数: 5

摘要

三模冗余(Triple Module Redundancy, TMR)加固方法是目前公认的防止电路软错误的最有效方法之一。然而，尽管降低软错误率(SER)不可避免地需要牺牲面积和功耗，但探索面积、功耗和SER之间权衡的优化方法却很少受到关注。因此，本研究借助神经网络算法和NSGA-II算法，研究了一种多目标优化模型，用于指导软误差免疫电路的设计。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Multi-objective Optimization Framework to Design Soft-Error-Immune Circuit

It is widely accepted that Triple Module Redundancy (TMR) hardened method is one of the most effective approach to protect circuit from soft error. However, while the mitigation of Soft Error Rate (SER) entails the inevitable sacrifice of area and power, little attention has been drawn to an optimization method to explore a trade-off between area, power and SER. Thus, with the help of neural network algorithm and NSGA-II algorithm, this study investigates a multi-objective optimization model as a guidance on Soft-Error-Immune circuit design.

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来源期刊

2019 19th European Conference on Radiation and Its Effects on Components and Systems (RADECS)

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