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Characterization of Library Cells for Open-circuit Defect Exposure: A Systematic Methodology

机译:开路缺陷曝光的图书馆细胞的表征:系统方法论

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Ensuring high defect coverage for advanced CMOS technology nodes has been a major challenge for the IC test industry. Traditional test methods using fault models such as stuck-at and transition faults with a primitive gate-level abstraction of design netlists have been shown to be inadequate for detecting open-circuit and short-circuit defects within instances of standard cells used in those netlists. Recent advances in Cell-Aware Test (CAT) using single pattern and two pattern tests have demonstrated increased coverage of such defects in industrial IC designs. However, the simulation overhead of defect characterization for all the cells in a library practically limits the size of defects that are explored to large magnitudes. Furthermore, certain effects such as charge sharing within cells can necessitate tests that span more than two time frames to expose subtle defects. This work, through simulation, identifies defects of certain sizes that can go undetected by current methods. It then proposes an algorithmic approach towards cell characterization that can result in faster identification of cell input stimuli vis-a-vis a defect simulation based method.
机译:确保高级CMOS技术节点的高缺陷覆盖是IC测试行业的重大挑战。已经显示使用诸如陷入困境和转换故障的故障模型的传统测试方法,该方法具有设计网级主义的原始门级抽象,用于检测在这些网手中使用的标准单元的实例中检测开路和短路缺陷。使用单个图案和两种模式测试的细胞感知测试(CAT)的最新进展已经表明了工业IC设计中这种缺陷的覆盖率增加。然而,库中所有单元的缺陷表征的模拟开销实际上限制了探索大量的缺陷的大小。此外,细胞内电荷共享的某些效果可能需要测试超过两个时间框架以暴露微妙的缺陷。这通过模拟来识别可以通过当前方法未被发现的某些尺寸的缺陷。然后,提出了一种旨在朝着细胞表征的算法方法,其可以导致基于缺陷仿真的细胞输入刺激的识别更快的识别。

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