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 fi...
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| Veröffentlicht in: | 37th Design Automation Conference, 2000 S. 671 - 674 |
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| Sprache: | Englisch |
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New York, NY, USA
ACM
01.01.2000
IEEE |
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| ISBN: | 9781581131871, 1581131879 |
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| Abstract | 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]. |
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| AbstractList | 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]. |
| Author | Kahng, Andrew B. Chen, Yu Zelikovsky, Alexander Robins, Gabriel |
| Author_xml | – sequence: 1 givenname: Yu surname: Chen fullname: Chen, Yu organization: UCLA Computer Science Dept., Los Angeles, CA – sequence: 2 givenname: Andrew B. surname: Kahng fullname: Kahng, Andrew B. organization: UCLA Computer Science Dept., Los Angeles, CA – sequence: 3 givenname: Gabriel surname: Robins fullname: Robins, Gabriel organization: Department of Computer Science, University of Virginia, Charlottesville, VA – sequence: 4 givenname: Alexander surname: Zelikovsky fullname: Zelikovsky, Alexander organization: Department of Computer Science, Georgia State University, Atlanta, GA |
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| Snippet | We propose practical iterated methods for layout density control for CMP uniformity, based on linear programming, Monte-Carlo and greedy algorithms. We... |
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| SubjectTerms | Applied computing -- Physical sciences and engineering -- Electronics Applied computing -- Physical sciences and engineering -- Engineering Chemical processes Computational geometry Computer science Filling Greedy algorithms Hardware -- Electronic design automation -- Physical design (EDA) Hardware -- Emerging technologies Hardware -- Robustness Hardware -- Very large scale integration design Linear programming Manufacturing processes Mathematics of computing -- Mathematical analysis -- Mathematical optimization -- Continuous optimization -- Linear programming Permission Semiconductor device modeling Solid modeling Theory of computation -- Design and analysis of algorithms -- Mathematical optimization -- Continuous optimization -- Linear programming |
| Title | Practical iterated fill synthesis for CMP uniformity |
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