A min-variance iterative method for fast smart dummy feature density assignment in chemical-mechanical polishing

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 2D 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(n³). Numerical experiments show the computational cost of our new method is almost negligible when compared with the LP method and its solution is very close to the optimal solution.