基于聚类技术和统计故障注入的人字拖seu选择性缓解

A. Evans, M. Nicolaidis, Shi-Jie Wen, Thiago Asis
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引用次数: 11

摘要

在大型soc中,管理人字拖中的软错误的影响是必不可少的,然而,有选择性的缓解是必要的,以尽量减少面积和功耗成本。确定要保护的最优触发器集通常需要计算密集型的故障注入活动。我们提出了新的技术,将相似的触发器分组成簇,以显着减少断层注入的数量。所需故障注入的数量可以显着低于触发器的总数,并且在一个超过100,000个触发器的工业设计中,通过仅模拟2,100个故障注入,该技术识别出一组4.1%的触发器,当受到保护时,将临界故障率降低了7倍。
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Clustering techniques and statistical fault injection for selective mitigation of SEUs in flip-flops
In large SoCs, managing the effects of soft-errors in flip-flops is essential, however, selective mitigation is necessary to minimize the area and power costs. The identification of the optimal set of flip-flops to protect typically requires compute-intensive fault-injection campaigns. We present new techniques which group similar flip-flops into clusters to significantly reduce the number of fault injections. The number of required fault injections can be significantly lower than the total number of flip-flops and in one industrial design with over 100,000 flip-flops, by simulating only 2,100 fault injections, the technique identified a set of 4.1% of the flip-flops, which when protected, reduced the critical failure rate by a factor of 7x.
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