Multi-objective optimization of interconnect geometry
The rapid increase in the number of wiring layers due to improved planarization and metallization techniques permits spatial resources to be traded for improved performance. Yield, power dissipation and propagation delay are all sensitive to the selection of the pitch and width of wires in each layer. As in many other engineering design problems, however, there exists no unique solution which simultaneously optimizes all aspects of system performance. The best that can be achieved is the identification of the optimal surface within the multi-objective performance space. A single design can be chosen from this list a posteriori using additional selection criteria which may depend, for example, on the specific details of the product application. This paper investigates the use of Pareto genetic algorithms to explore the extent of multi-objective optimal surfaces. The tradeoffs between yield, power-dissipation and cycle time for a benchmark netlist are examined as a function of in-plane geometry for a seven-layer interconnect.
interconnect genetic algorithms pareto optimization vlsi