A performance-driven fuzzy algorithm for placement of macro cells

Abstract

Macro cell placement is an integral part of VLSI design. Existing placement techniques do not use a realistic human-like intuitive process for making decisions and therefore, lack the ability to make decisions based on several factors at once. In this research a quad-partitioning algorithm with a tabu search and a fuzzy cost function is used for macro cell placement. This approach partitions the design into small pieces that can be easily placed. The algorithm is based on a method which tries to reduce the path lengths and reduce the number of edges which cross out of a partition. The fuzzy cost function adds the human reasoning missing from other algorithms. The algorithm allows I/O cells to be preplaced or it can optimize their placement. The results show that this algorithm produces higher quality placements than other macro cell algorithms such as Lim, Chee and Wu and Lin and Du.