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Statistical timing verification for transparently latched circuits

机译:透明锁存电路的统计时序验证

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摘要

High-performance integrated-circuit designs need to verify the clock schedules as they usually have level-sensitive latches for their speed. With process variations, the verification needs to compute the probability of correct clocking. Because of complex statistical correlations and accumulated inaccuracy of statistical operations, traditional iterative approaches have difficulties in getting accurate results. A statistical check of the structural conditions for correct clocking is proposed instead, where the central problem is to compute the probability of having a positive cycle in a graph with random edge weights. The authors proposed two algorithms to handle this. The proposed algorithms traverse the graph only several times to reduce the correlations among iterations, and it considers not only data delay variations but also clock-skew variations. Although the first algorithm is a heuristic algorithm that may overestimate timing yields, experimental results show that it has an error of 0.16% on average in comparison with the Monte Carlo (MC) simulation. Based on a cycle-breaking technique, the second heuristic algorithm can conservatively estimate timing yields. Both algorithms are much more efficient than the MC simulation.
机译:高性能集成电路设计需要验证时钟调度,因为它们通常具有电平敏感的锁存器以提高速度。随着工艺的变化,验证需要计算正确计时的概率。由于复杂的统计相关性和统计操作的累积误差,传统的迭代方法很难获得准确的结果。取而代之的是,提出了对用于正确计时的结构条件的统计检查,其中的中心问题是计算在具有随机边缘权重的图形中具有正周期的概率。作者提出了两种算法来处理此问题。所提出的算法仅遍历图几次以减少迭代之间的相关性,并且它不仅考虑数据延迟变化,而且考虑时钟偏斜变化。尽管第一种算法是一种启发式算法,可能会高估时序收益,但实验结果表明,与蒙特卡洛(MC)仿真相比,其平均误差为0.16%。基于周期中断技术,第二种启发式算法可以保守地估计时序收益。两种算法都比MC仿真有效得多。

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