Statistic Analysis of Power/Ground Networks Using Single-Node SOR Method
Statistic Analysis of Power/Ground Networks Using Single-Node SOR Method
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DOI：
10.1109/isqed.2008.62
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发表时间：
2008-03
期刊：
影响因子：
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通讯作者：
Zuying Luo;S. Tan
中科院分区：
文献类型：
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作者：
Zuying Luo;S. Tan
在本文中，我们提出了一种有效的统计分析方法分析芯片上的电源网格。新的方法，称为SN-SOR（及其更快的版本，PSN- SOR），是基于一种新的局部松弛迭代方法，它可以执行变分分析的一个节点上的时间。PSN-SOR通过使用改进的条件进一步加快了分析速度，其中SN-SOR的初始解用作后续迭代的预条件。实验结果表明，PSN-SOR比Monte-Carlo方法快约两个数量级（186倍），最大误差小于5.685%，比一般的全局逐次超松弛（SOR）方法快约一个数量级（41倍）。PSN-SOR比最近提出的局部统计分析的随机游走方法更准确和有效。
In this paper, we propose an efficient statistical analysis method for analyzing on-chip power grids. The new method, called SN-SOR (and its faster version, PSN- SOR), is based on a novel localized relaxed iterative approach and it can perform variational analysis on one node at a time. PSN-SOR further speeds up the analysis by using a refined conditioner, where the initial solution of SN-SOR is used as the pre-conditioner for the later iterations. Experimental results show that PSN-SOR is about two orders of magnitude(186X) faster than Monte- Carlo method with slight errors less than 5.685% on maximum and is about one order magnitude (41X) faster than general global successive over relaxation (SOR) method. PSN-SOR is more accurate and efficient than the recently proposed random walk method for localized statistical analysis.