Defect and Variation Issues on Design Mapping of Reconfigurable Nanoscale Crossbars

High defect density and extreme process variation for nanoscale self-assembled crossbar-based architectures have been expected to be as fundamental design challenges. Consequently, defect and variation issues must be considered on logic mapping on nanoscale crossbars. In this paper, we investigate a greedy algorithm for the variation and defect aware logic mapping of crossbar arrays. Based on Mont-Carlo simulation, we compare the proposed technique with other logic mapping techniques such as variation unaware and exhaustive search mapping in terms of accuracy as well as runtime.