Fuzzy partitioning applied to VLSI-floorplanning and placement

Fast hierarchical optimization methods applied to VLSI-floorplanning and placement play a major role in advancing the state of the art in physical design, because circuits get more and more complex. This paper presents a new approach for floorplanning and placement using fuzzy logic as the framework for optimal partitioning. Two hierarchical partitioning strategies are described, both based on the fuzzy c-means algorithm (FCM), well known in the area of clustering and pattern recognition. The first method outlined is applied to a modified GORDIAN procedure, combining wire-length minimization by force directed relaxation (FDR) and a fast clustering technique instead of min-cut. The second approach outlined specifies different similarities between the cells using one fuzzy similarity relation for each feature. A simple example with 16 mesh connected cells and a benchmark example with 33 cells are given to demonstrate the performance of the strategy