面向复杂设计中see诱发失效的优化功能评估

D. Alexandrescu, Enrico Costenaro
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引用次数: 16

摘要

单事件效应强烈影响电子电路和系统的可靠性,需要仔细的SER表征和适当规模的缓解策略。SER研究旨在提供电路在特定工作环境下的相关信息,如功能故障率、临界性等。最终,减少错误的努力是通过降低故障发生率或故障影响来改善电路在SEE存在下的功能。然而,当处理影响高度复杂电子设计的see时,功能问题是最复杂的方面之一,难以可靠地表征。本文旨在提出和评估几种故障表征技术,旨在在设计流程的早期近似复杂电路中由单事件中断引起的功能故障。我们的两个主要贡献包括基于标准仿真工具的差分故障仿真方法和一种新的并行的、优化的、独立的仿真工具。这两种方法都能准确地评估see引起的故障的即时传播,并预测故障电路运行特定应用的长期行为。本文中描述的工作还受益于各种优化技术,旨在降低模拟成本(在CPU和人力方面),同时保持结果的准确性。最后,每种方法的结果都与从详尽故障模拟活动中获得的参考数据进行了正面比较。这一令人鼓舞的结果表明,在花费合理的资源(CPU、人力和时间)的同时,我们可以可靠地获得信息丰富的功能错误信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards optimized functional evaluation of SEE-induced failures in complex designs
Single Event Effects strongly impact the reliability of electronic circuits and systems, requiring careful SER characterization and adequately sized mitigation strategy. The SER study aims at providing relevant information about the circuit behavior in the specified working environment, in terms of Functional Failures rates, criticality and so on. Ultimately, the error mitigation efforts are directed at improving the function of the circuit in the presence of SEE by either reducing the failure occurrence rate or the failure impact. However, when dealing with SEEs affecting highly sophisticated electronic designs, functional issues are one of the most complex aspects to reliably characterize. This paper aims at proposing and evaluating several fault characterization techniques, meant to approximate the functional failures induced by Single Event Upsets in complex circuits, very early in the design flow. The two main contributions of our efforts consist in a differential fault simulation approach based on standard simulation tools and a novel parallel, SEE-optimized, stand-alone simulation tool. Both methods accurately evaluate the immediate propagation of SEE-induced faults and predict the long-term behavior of the faulty circuit running a specified application. The works described in this paper also benefit from various optimization techniques targeting lower simulation costs (in terms of CPU and man-power) while preserving the accuracy of the results. Ultimately, the results of each method compare positively with reference data obtained from an exhaustive fault simulation campaign. This encouraging outcome suggests that we can reliably obtain highly informative functional error information while spending reasonable resources (CPU, man-power, time).
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