On N-detect pattern set optimization

Yu Huang
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引用次数: 31

Abstract

In this paper, we illustrate that the traditional N-detect ATPG is unoptimized in terms of the size of the generated pattern set. The optimization problem is formulated as a minimum covering problem. Integer linear programming (ILP) is applied to obtain an N-detection ATPG pattern set with the minimum number of patterns. A heuristic method is also proposed to obtain sub-optimal solutions efficiently. Experimental results demonstrate that by using the proposed method, the number of N-detection patterns can be reduced by about 18% for N=3 and about 13% for N=5 without compromising N-detection objective
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关于n检测模式集的优化
在本文中,我们说明了传统的N-detect ATPG在生成模式集的大小方面是未优化的。将优化问题表述为最小覆盖问题。采用整数线性规划(ILP)方法,得到了具有最小模式数的n检测ATPG模式集。提出了一种启发式方法来有效地获得次优解。实验结果表明,采用该方法,在不影响N检测目标的情况下,当N=3时,N检测模式的数量可减少约18%,当N=5时可减少约13%
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