Efficient Approximation Algorithms for Chemical Mechanical Polishing Dummy Fill

To reduce chip-scale topography variation in chemical mechanical polishing process, dummy fill is widely used to improve the layout density uniformity. Previous researches formulated the density-driven dummy fill problem as a standard linear program (LP). However, solving the huge linear program for...

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Bibliographic Details
Published in:IEEE transactions on computer-aided design of integrated circuits and systems Vol. 30; no. 3; pp. 402 - 415
Main Authors: Feng, Chunyang, Zhou, Hai, Yan, Changhao, Tao, Jun, Zeng, Xuan
Format: Journal Article
Language:English
Published: New York IEEE 01.03.2011
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithm design and analysis
Algorithms
Approximation
Approximation algorithms
Approximation methods
Capacitance
Coupling capacitance
Couplings
covering linear programming
Design engineering
design for manufacturability
Dummies
dummy fill problem
Heuristic
Joining
Layout
Mathematical analysis
Monte Carlo methods
Operations research
Upper bound
ISSN:0278-0070, 1937-4151
Online Access:Get full text
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Summary:To reduce chip-scale topography variation in chemical mechanical polishing process, dummy fill is widely used to improve the layout density uniformity. Previous researches formulated the density-driven dummy fill problem as a standard linear program (LP). However, solving the huge linear program formed by real-life designs is very expensive and has become the hurdle in deploying the technology. Even though there exist efficient heuristics, their performance cannot be guaranteed. Furthermore, dummy fill can also change the interconnect coupling capacitance which might lead to a significant influence on circuit delay, crosstalk, and power consumption. In this paper, we develop a dummy fill algorithm that can be applied to solve both the traditional density-driven problem and the problem considering fill-induced coupling capacitance impact. The proposed algorithm is both efficient and with provably good performance, which is based on a fully polynomial time approximation scheme by Fleischer for covering LP problems. Moreover, based on the approximation algorithm, we also propose a new greedy iterative algorithm to achieve high quality solutions more efficiently than previous Monte Carlo based heuristic methods. Final experimental results demonstrate the effectiveness and efficiency of our algorithms.
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ISSN:0278-0070
1937-4151
DOI:10.1109/TCAD.2010.2088030