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Accurate and Efficient Estimation of Logic Circuits Reliability Bounds

机译:逻辑电路可靠性界的准确而有效的估计

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As the sizes of CMOS devices rapidly scale deep into the nanometer range, the manufacture of nanocircuits will become extremely complex and will inevitably introduce more defects, including more transient faults that appear during operation. For this reason, accurately calculating the reliability of future designs will be extremely critical for nanocircuit designers as they investigate design alternatives to optimize the tradeoffs between area-power-delay and reliability. However, accurate calculation of the reliability of large and highly connected circuits is complex and very time consuming. This paper presents a complete solution for estimating logic circuit reliability bounds with high accuracy in reasonable time, even for very large and complex circuits. The solution combines a novel criticality scoring algorithm to rank the reliability of individual input vectors with a heuristic search to find the input vector having the lowest reliability. The solution scales well with circuit size, and is independent of the interconnect complexity or the logic depth. Extensive computational results show that the speed of our method is orders of magnitude faster than exact solutions provided by Bayesian network exact inferences, while maintaining identical or sufficiently close accuracy.
机译:随着CMOS器件的尺寸迅速扩展到纳米范围,纳米电路的制造将变得极其复杂,并且不可避免地会引入更多的缺陷,包括在操作过程中出现的更多瞬态故障。由于这个原因,对于纳米电路设计人员来说,准确地计算未来设计的可靠性至关重要,因为他们正在研究设计方案以优化面积功耗延迟和可靠性之间的权衡。但是,对大型且高度连接的电路的可靠性进行精确计算是复杂且非常耗时的。本文提出了一个完整的解决方案,即使在非常大和复杂的电路中,也可以在合理的时间内以高精度估算逻辑电路的可靠性范围。该解决方案结合了一种新颖的关键性评分算法,通过启发式搜索对单个输入向量的可靠性进行排名,以找到具有最低可靠性的输入向量。该解决方案可根据电路大小很好地扩展,并且与互连复杂性或逻辑深度无关。大量的计算结果表明,我们的方法的速度比贝叶斯网络精确推论提供的精确解要快几个数量级,同时保持相同或足够接近的准确性。

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