A Network-Flow Based Cell Sizing Algorithm

We propose a timing-driven discrete cellsizing algorithm that can incorporate total cell size constraints. We model cell sizing as a min-cost network flow problem. In the network flow graph, available sizes of each cell are modeled as nodes. Flow passing through a node indicates the choice of the corresponding cell size, and the total flow cost reflects the timing objective function value change with the chosen sizes of cells. Compared to other discrete optimization methods for cell sizing, our method can obtain a near-optimal solution in a very timeefficient manner. We tested our algorithm on the ISCAS’85 benchmark, and compared our results with an optimal solution produced by an exhaustive search method with exponential time complexity. The results show that given the same initial sizing, the improvement obtained by our method is only 1% worse (11.9% v.s. 12.9%) than the optimal solution, while satisfying a given total cell area constraint. Furthermore, our method is 60 times faster than the optimal method.