超大规模集成电路分析中时间分辨成像的聚类匹配

S. Chef, S. Jacquir, P. Perdu, K. Sanchez, S. Binczak
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引用次数: 4

摘要

如果说规模化的好处是让制造商能够设计出未来的集成电路,那么从故障分析的角度来看,它也有一个缺点,那就是让设备变得更复杂。现代VLSI的测试序列可能相当长,有数千个向量。动态光子发射数据库可以包含数百万个光子,代表感兴趣区域的数千个状态变化。寻找执行物理分析的候选位置非常具有挑战性,特别是如果故障发生在单个矢量上。本文提出了一种动态光子发射数据库中单矢量故障的新方法。该过程应用于采集后水平,并基于聚类算法和最近邻研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cluster matching in time resolved imaging for VLSI analysis
If scaling has the benefit of enabling manufacturers to design tomorrow's integrated circuits, from the failure analyst point of view it also has the drawback of making devices more complex. The test sequence for modern VLSI can be quite long, with thousands of vector. Dynamic photon emission databases can contain millions of photons representing thousands of state changes in the region of interest. Finding a candidate location where to perform physical analysis is quite challenging, especially if the fault occurs on a single vector. In this paper, we suggest a new methodology to find single vector fault in dynamic photon emission database. The process is applied at the post-acquisition level and is based on clustering algorithm and nearest neighbor research.
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