The Use of Genetic Algorithm to Derive Correlation Between Test Vector and Scan Register Sequences and Reduce Power Consumption

Z. Kotásek, Jaroslav Skarvada, Josef Strnadel
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引用次数: 2

Abstract

In most of existing approaches, the reorganization of test vector sequence and reordering scan chains registers to reduce power consumption are solved separately, they are seen as independent procedures. In the paper it is shown that a correlation between these two processes and strong reasons to combine them into one procedure run concurrently exist. Based on this idea, it is demonstrated that search spaces of both procedures can be combined together into a single search space in order to achieve better results during the optimization process. The optimization over the united search space was tested on ISCAS85, ISCAS89 and ITC99 benchmark circuits implemented by means of CMOS primitives from AMI technological libraries. Results presented in the paper show that lower power consumption can be achieved if the correlation is reflected, i.e., if the search space is united rather than divided into separate spaces. At the end of the paper, results achieved by genetic algorithm based optimization are presented, discussed and compared with results of existing methods.
利用遗传算法推导测试向量和扫描寄存器序列之间的相关性,降低功耗
在现有的方法中,为了降低功耗,测试向量序列的重组和扫描链寄存器的重新排序是分开解决的,它们被看作是独立的过程。本文证明了这两个过程之间存在相关性,并有充分的理由将它们合并为一个过程并发运行。在此基础上,证明了在优化过程中,为了获得更好的结果,可以将两个过程的搜索空间组合成一个搜索空间。在ISCAS85、ISCAS89和ITC99基准电路上,利用AMI技术库中的CMOS原语实现了统一搜索空间的优化。本文的研究结果表明,如果反映相关性,即如果将搜索空间统一起来而不是分割成单独的空间,则可以实现更低的功耗。最后给出了基于遗传算法的优化结果,并与现有方法的结果进行了讨论和比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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