Linear decomposition algorithm for VLSI design applications

We propose a unified solution to both linear placement and partitioning. Our approach combines the well-known eigenvector optimization method with the recursive max-flow min-cut method. A linearized eigenvector method is proposed to improve the linear placement. A hypergraph max algorithm is then adopted to efficiently find the max-flow min-cut. In our unied approach, the max-flow min-cut provides an optimal ordered partition subject to the given seeds and the eigenvector placement provides heuristic information for seed selection. Experimental results on MCNC benchmarks show that our approach is superior to other methods for both linear placement and partitioning problems. On average, our approach yields an improvement of 45.1 % over eigenvector approach in terms of total wire length, and yields an improvement of 26.9 % over PARABOLI[6] in terms of cut size.