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Minimizing Soft Errors in TCAM Devices: A Probabilistic Approach to Determining Scrubbing Intervals

机译:最小化TCAM设备中的软错误:一种确定擦洗间隔的概率方法

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Ternary content addressable memory (TCAM) is more susceptible to soft errors than static random access memory (SRAM). The large di/dt issue during comparison operation reduces operating voltage ranges, which in turn reduces soft error immunity. The tight structural coupling of TCAM comparison circuits and memory cells does not allow for an interleaving design scheme in mitigating soft errors. Regular scrubbing of stored content can greatly mitigate the reliability issue caused by soft errors. However, frequent scrubbing can also affect device performance. The scrubbing interval should be determined to facilitate both reliability and performance. This paper proposes a novel, model-based approach that includes both single-bit upsets (SBUs) and multi-cell upsets (MCUs) to determine the scrubbing interval by predictive and probabilistic failure rate analysis. This model uses the compound Poisson (CP) process to count clustered random events, which are common phenomena of soft errors in technologies that use chips under 90 nm. The 20 M TCAM with 90-nm CMOS technology was tested with 180-MeV neutron strikes. The scrubbing interval determined based on the proposed model is applied to the TCAM test results. The failure probabilities based on the CP model showed 31% overestimation on average compared to the same from the test data. Such overestimation is mainly due to the independent upset assumption in the proposed model and can enable use of the model as worst case analysis. The worst case comparison with the test data showed 1.7% overestimation, which can tell the proposed model is effective in predicting upper-bound soft error reliability.
机译:三元内容可寻址存储器(TCAM)比静态随机存取存储器(SRAM)更容易受到软错误的影响。比较操作期间较大的di / dt问题减小了工作电压范围,进而降低了抗软错误性。 TCAM比较电路和存储单元的紧密结构耦合不允许在减轻软错误方面采用交错设计方案。定期清理存储的内容可以极大地减轻由软错误引起的可靠性问题。但是,频繁的擦洗也会影响设备性能。应该确定擦洗间隔以促进可靠性和性能。本文提出了一种新颖的,基于模型的方法,该方法同时包含单比特翻转(SBU)和多单元翻转(MCU),以通过预测性和概率故障率分析来确定清理间隔。该模型使用复合泊松(CP)过程来计算聚集的随机事件,这是使用90 nm以下芯片的技术中常见的软错误现象。具有90 nm CMOS技术的20 M TCAM已通过180 MeV中子撞击进行了测试。基于建议的模型确定的洗涤间隔将应用于TCAM测试结果。与测试数据相比,基于CP模型的故障概率平均高估了31%。这种高估主要归因于所提出模型中的独立up陷假设,并且可以使该模型能够用作最坏情况分析。最坏情况下与测试数据的比较显示出1.7%的高估,这可以表明所提出的模型对于预测上限软错误可靠性是有效的。

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