百万栅极大型电路的故障字典缩减

Y. Hong, Juinn-Dar Huang
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引用次数: 6

摘要

一般情况下,故障字典的体积太大,不利于实际应用。在减小故障字典大小方面,前人提出了一些研究成果。然而,由于高时间和空间复杂性,它们可能无法处理当今的百万栅极电路。在本文中,我们提出了一种算法,以显著减少故障字典的大小,同时仍保持较高的诊断分辨率。该算法避免了构造庞大的可区分性表,因而具有极低的时间和空间复杂度,而这必然会增加所需的计算量。实验结果表明,该算法完全能够在合理的运行时间和内存范围内处理工业百万门大型电路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault Dictionary Size Reduction for Million-Gate Large Circuits
In general, fault dictionary is prevented from practical applications for its extremely large size. Several previous works are proposed for the fault dictionary size reduction. However, they might not be able to handle today's million-gate circuits due to the high time and space complexity. In this paper, we propose an algorithm to significantly reduce the size of fault dictionary while still preserving high diagnostic resolution. The proposed algorithm possesses extremely low time and space complexity by avoiding constructing the huge distinguishability table, which inevitably boosts up the required computation complexity. Experimental results demonstrate that the proposed algorithm is fully capable of handling industrial million-gate large circuits in a reasonable amount of runtime and memory.
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