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DAC
2000
ACM

Practical iterated fill synthesis for CMP uniformity

14 years 4 months ago
Practical iterated fill synthesis for CMP uniformity
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 MonteCarlo 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].
Yu Chen, Andrew B. Kahng, Gabriel Robins, Alexande
Added 13 Nov 2009
Updated 13 Nov 2009
Type Conference
Year 2000
Where DAC
Authors Yu Chen, Andrew B. Kahng, Gabriel Robins, Alexander Zelikovsky
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