A new paradigm for trading off yield, area and performance to enhance performance per wafer

In this paper we outline a novel way to 1) predict the revenue associated with a wafer, 2) maximize the projected revenue through unconventional yield enhancement techniques, and 3) produce dice from the same mask that may have different performances and selling prices. Unlike speed binning, such heterogeneity is intentional by design. To achieve these goals we overturn the traditional concepts of redundancy, and present a novel design flow for yield enhancement called "Reduced Redundancy Insertion", where spares can potentially have less area and performance than their fathers. We develop a model for the revenue associated with the new design methodology that integrates system configuration and leverages yield, area and performance. The primary metric used in this model is termed "Expected Performance per Area", which is a measure that can be reliably estimated for different system architectures, and can be maximized by using algorithms proposed in this paper. We present theoretical models and case studies that characterize our designs, and experimental results that validate our prediction. We show that using Reduced Redundancy can improve wafer revenue by 10-30%.