Practical iterated fill synthesis for CMP uniformity
Practical iterated fill synthesis for CMP uniformity
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DOI：
10.1145/337292.337610
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发表时间：
2000-06
期刊：
影响因子：
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通讯作者：
Yu Chen;A. Kahng;G. Robins;A. Zelikovsky
中科院分区：
文献类型：
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作者：
Yu Chen;A. Kahng;G. Robins;A. Zelikovsky
We propose practical iterated methods for layout density control for CMP uniformity, based on linear programming, Monte-Carlo and greedy algorithms. We experimentally study the tradeoffs between two main filling objectives: minimizing density variation, and minimizing the total amount of inserted fill. Comparisons with previous filling methods show the advantages of our new iterated Monte-Carlo and iterated greedy methods. We achieve near-optimal filling with respect to each of the objectives and for both density models (spatial density [3] and effective density [8]). Our new methods are more efficient in practice than linear programming [3] and more accurate than non-iterated Monte-Carlo approaches [1].
