Defect tolerant probabilistic design paradigm for nanotechnologies

Recent successes in the development and self-assembly of nanoelectronic devices suggest that the ability to manufacture dense nanofabrics is on the near horizon. However, the tremendous increase in device density of nanoelectronics will be accompanied by a substantial increase in hard and soft faults, posing a major challenge to current design methodologies and tools. In this paper we propose a novel probabilistic design paradigm for defective but reconfigurable nanofabrics. The new design goal is to devise an appropriate structural/behavioral decomposition which improves scalability by constraining the reconfiguration process, while meeting a desired probability of successful instantiation, i.e, yield. Our approach not only addresses the scalability problem in configuring dense nanofabrics subject to defects, but gives a rich framework in which critical trade-offs among performance, yield, and per chip cost can be explored. We present a concrete instance of the approach and show extensive experimental results supporting these claims.