VLSI yield optimization based on the sub-processing-element level redundancy

An optimal allocation model of the sub-processing-element (sub-PE) level redundancy is developed by using a genetic algorithm. The average defect density D and the support circuit parameter δ are considered in this allocation model to accurately analyze the element yield. Under the condition of the given area constraint, simulation results indicate that the number of the optimal redundant sub-circuits added to a PE and the PE´s yield are decrease for any given average defect density D as δ increase. Further, the number of the optimal redundant sub-circuits is increase, while the optimal yield of the PE is decrease for any given support circuit area parameter δ as D increases