Practical iterated fill synthesis for CMP uniformity
Proceedings of the 37th Annual Design Automation Conference
Monte-Carlo algorithms for layout density control
ASP-DAC '00 Proceedings of the 2000 Asia and South Pacific Design Automation Conference
Reticle enhancement technology: implications and challenges for physical design
Proceedings of the 38th annual Design Automation Conference
Filling algorithms and analyses for layout density control
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Model-based dummy feature placement for oxide chemical-mechanical polishing manufacturability
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Area fill synthesis for uniform layout density
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Is your layout density verification exact?: a fast exact algorithm for density calculation
Proceedings of the 2007 international symposium on Physical design
A methodology for fast and accurate yield factor estimation during global routing
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Novel wire density driven full-chip routing for CMP variation control
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Provably good and practically efficient algorithms for CMP dummy fill
Proceedings of the 46th Annual Design Automation Conference
A novel wire-density-driven full-chip routing system for CMP variation control
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Dummy feature filling is an efficient approach for reducing wafer-topography variation in chemical-mechanical polishing (CMP), which is the key planarization process in modern VLSI fabrication. In this paper, we present a new min-variance iterative method for fast smart dummy feature density assignment and post-CMP topography variation reduction. This method iteratively selects target areas using an efficient CMP low-pass filter model and a variance-minimizing heuristic, and assigns/removes dummy features accordingly. Because of the efficient usage of the 2-D Fast Fourier Transform (FFT), the computational cost of this new method is close to O(nlog(n)), making it much faster than the existing linear programming method that costs O(n^3 ). Numerical experiments show the computational cost of our new method is almost negligible when compared with the LPmethod and its solution is very close to the optimal solution.