Multiple fault diagnosis in crossbar nano-architectures

Bottom up self-assembly of nano-crossbars from carbon nano-tubes and semiconductor nano-wires has shown the potential to overcome the limitations of lithographic fabrication of CMOS for further down-scaling. However, very high permanent and transient fault rates necessitates the incorporation of efficient fault tolerance techniques, capable of handling multiple faults. Self repair provides fault tolerance through fault detection, diagnosis and reconfiguration to recover from permanent faults. In this paper, we present a multiple faults diagnosis scheme based on dual rail error checking frameworks for nano-crossbar architectures. The proposed scheme is capable of identifying multiple faulty crosspoints with very low performance and area overheads. The experimental results show that all of the multiple faults are correctly diagnosed.