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Simultaneous Buffer Insertion and Wire Sizing Considering Systematic CMP Variation and Random $L_{rm eff}$ Variation

机译:同时考虑系统CMP变异和随机$ L_ {rm eff} $变异的同时插入缓冲区和调整导线大小

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This paper presents extensions of the dynamic-programming (DP) framework to consider buffer insertion and wire-sizing under effects of process variation. We study the effectiveness of this approach to reduce timing impact caused by chemical-mechanical planarization (CMP)-induced systematic variation and random Leff process variation in devices. We first present a quantitative study on the impact of CMP to interconnect parasitics. We then introduce a simple extension to handle CMP effects in the buffer insertion and wire sizing problem by simultaneously considering fill insertion (SBWF). We also tackle the same problem but with random Leff process variation (vSBWF) by incorporating statistical timing into the DP framework. We develop an efficient yet accurate heuristic pruning rule to approximate the computationally expensive statistical problem. Experiments under conservative assumption on process variation show that SBWF algorithm obtains 1.6% timing improvement over the variation-unaware solution. Moreover, our statistical vSBWF algorithm results in 43.1% yield improvement on average. We also show that our approaches have polynomial time complexity with respect to the net-size. The proposed extensions on the DP framework is orthogonal to other power/area-constrained problems under the same framework, which has been extensively studied in the literature
机译:本文介绍了动态编程(DP)框架的扩展,以考虑在工艺变化的影响下缓冲器的插入和线径的确定。我们研究这种方法的有效性,以减少由化学机械平面化(CMP)引起的系统变化和器件中的随机Leff工艺变化引起的时序影响。我们首先对CMP对互连寄生效应的影响进行定量研究。然后,我们引入一个简单的扩展,通过同时考虑填充插入(SBWF)来处理缓冲区插入和导线尺寸确定问题中的CMP效应。我们还通过将统计时序纳入DP框架来解决相同的问题,但随机Leff过程变化(vSBWF)。我们开发了一种有效而准确的启发式修剪规则,以近似计算量大的统计问题。在保守的过程变化假设下进行的实验表明,SBWF算法比无变化解决方案的时序改进了1.6%。此外,我们的统计vSBWF算法平均可将产量提高43.1%。我们还表明,相对于网络大小,我们的方法具有多项式时间复杂度。在DP框架上建议的扩展与同一框架下的其他受功率/区域限制的问题正交,在文献中对此进行了广泛的研究。

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