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CONCAT: CONflict Driven Learning in ATPG for Industrial designs

机译:CONCAT:冲突驱动ATPG的工业设计学习

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In this paper, we propose a new search technique for ATPG, called CONCAT [1], which (a) is based on AND/OR reasoning, (b) integrates conflict driven learning, and (c) avoids over specification of test vectors. The technique works seamlessly (i) between Boolean and non-Boolean gates in industrial designs, (ii) across phases in latch-based designs, (iii) between justification and propagation tasks in sequential ATPG, and (iv) across faults in the fault list. Experimental results on combinational ISCAS circuits against SAT-based ATPG, show that we can reduce the test vector specification by upto 74%, with consistent improvement in performance and capacity. We integrated the CONCAT technique into Intel's existing ATPG tool, called Aztec, and obtained upto 67% speed-up and upto 14% more ATPG effectiveness on industrial designs.
机译:在本文中,我们向ATPG提出了一种新的搜索技术,称为Concat [1],(a)基于和/或推理,(b)集成冲突驱动的学习,(c)避免了测试向量的规范。该技术在工业设计中的布尔和非布尔盖板之间无缝(i)在锁存的设计中的阶段(ii)之间的工作(iii)在顺序ATPG中的正义和传播任务之间的阶段(iii)之间的阶段(iii)之间的工作组成列表。对基于SAT的ATPG组合ISCAS电路的实验结果表明,我们可以将测试矢量规范降低到74%,性能和容量的一致性提高。我们将Concat技术集成到英特尔现有的ATPG工具中,称为AZTEC,并获得高达67%的加速,高达14%的工业设计的ATPG效力。

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