Improving Performance and Routability Estimation in Deep-submicron Placement 1

Placement of multiple dies on an MCM or high-performance VLSI substrate is a non-trivial task in which multiple criteria need to be considered simultaneously to obtain a true multi-objective optimization. Unfortunately, the exact physical attributes of a design are not known in the placement step until the entire design process is carried out. When the performance issues are considered, crosstalk noise constraints in the form of net separation and via constraint become important. In this paper, for better performance and wirability estimation during placement for MCMs, several performance constraints are taken into account simultaneously. A graph-based wirability estimation along with the Genetic placement optimization technique is proposed to minimize crosstalk, crossings, wirelength and the number of layers. Our work is signiicant since it is the rst attempt at bringing the crosstalk and other performance issues into the placement domain.