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Optimal multi-row detailed placement for yield and model-hardware correlation improvements in sub-10nm VLSI

机译:低于10nm VLSI的最佳多行详细放置以提高良率和模型硬件相关性

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In sub-10nm, nodes, a change or step in diffusion height between adjacent standard cells causes yield loss as well as a form of model-hardware miscorrelation called neighbor diffusion effect (NDE). Cell libraries must inevitably have multiple diffusion heights (numbers of fins in PFETs and NFETs) in order to enable flexible exploration of the power-performance envelope for design. However, this brings step-induced risks of NDE, for which guardbanding is costly, as well as yield loss. Special filler cells can protect against harmful NDE effects, but are costly in terms of area. In this work, we develop dynamic programming-based single-row and double-row detailed placement optimizations that optimally minimize the impacts of NDE. Our algorithms support a richer set of cell movements than in previous works - i.e., flipping, relocating and reordering within the original row; we also consider cell displacement and flipping costs. Importantly, to our knowledge, our dynamic programming-based optimal detailed placement algorithm is the first to handle multiple rows with multiple-height cells that can be reordered. We further develop a timing-aware approach, which is capable of recovering (or, improving) the worst negative slack (WNS) by creating additional diffusion steps around timing-critical cells.
机译:在低于10nm的节点中,相邻标准单元之间扩散高度的变化或阶跃会导致良率损失以及一种称为邻居扩散效应(NDE)的模型-硬件​​不相关形式。单元库必须不可避免地具有多个扩散高度(PFET和NFET中的鳍片数量),以便能够灵活地探索设计的功率性能范围。但是,这带来了逐步诱发的NDE风险,因为保护带成本高昂,并且损失了产量。特殊的填充电池可以防止有害的NDE效应,但是面积大。在这项工作中,我们开发基于动态编程的单行和双行详细布局优化,以最大程度地减小NDE的影响。与以前的工作相比,我们的算法支持更丰富的单元格移动集-即在原始行内翻转,重新定位和重新排序;我们还考虑了单元移位和翻转成本。重要的是,据我们所知,我们基于动态编程的最佳详细位置算法是第一个处理具有多高度单元格(可以重新排序)的多行的算法。我们进一步开发了一种时序感知方法,该方法能够通过在时序关键单元周围创建其他扩散步骤来恢复(或改善)最严重的负松弛(WNS)。

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