基于图划分的小延迟缺陷检测路径选择

Zijian He, Tao Lv, Huawei Li, Xiaowei Li
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引用次数: 8

摘要

关键路径选择在小延迟缺陷(SDD)测试中起着重要的作用。对于某些时序平衡电路,候选关键路径的数量可能非常大,这将使基于蒙特卡罗仿真的统计时序分析效率非常低。提出了一种基于图划分的快速路径选择方法。首先生成一个隐式枚举几乎所有候选关键路径的关键路径图(CPG),然后使用两种图划分方法将关键路径图划分为包含有限路径数的子图。然后对每个子图进行蒙特卡罗模拟,进行路径选择。最后,根据CPG的分区拓扑和从每个子图中选择的路径集,使用并集和笛卡尔积运算生成原始CPG的路径集,用于测试sdd。实验结果表明,对于包含大量候选关键路径的电路,与基于一般蒙特卡罗仿真的路径选择方法相比,所提出的路径选择方法可以显著减少CPU时间,并保持更高的捕获延迟故障的概率。
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Graph partition based path selection for testing of small delay defects
Critical path selection plays an important role in testing of small delay defects (SDD). For some timing-balanced circuits, the numbers of candidate critical paths may be very large, and this will make Monte Carlo simulation based statistical timing analysis very inefficient. A fast path selection approach based on graph partition is proposed in this paper. First, a critical path graph (CPG) is generated to implicitly enumerate almost all candidate critical paths, and then the CPG is partitioned into several sub graphs which contain limited numbers of paths using two graph partition approaches. After that, Monte Carlo simulation is applied on each sub graph for path selection. At last, according to the partition topology of the CPG and path sets selected from each sub graph, a path set for the original CPG is generated using Union and Cartesian product operations for testing SDDs. Experimental results show that for circuits containing large numbers of candidate critical paths, the proposed path selection approach can reduce the CPU time significantly and maintain a higher probability of capturing delay failures compared to path selection methods based on general Monte Carlo simulation.
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