Online multiple error detection in crossbar nano-architectures

Crossbar nano-architectures based on self-assembled nano-structures are promising alternatives for current CMOS technology, which is facing serious challenges for further down-scaling. One of the major challenges in this nanotechnology is elevated failure rate due to atomic device sizes and inherent lack of control in self-assembly fabrication. Therefore, high permanent and transient failure rates lead to multiple faults during lifetime operation of crossbar nano architectures. In this paper, we present a concurrent multiple error detection scheme for multistage crossbar nano-architectures based on dual-rail implementations of logic functions. We prove the detectability of all single faults as well as most classes of multiple faults in this scheme. Based on statistical multiple fault injection, we compare the proposed technique with other online error detection and masking techniques such as Triple Module Redundancy (TMR), duplication, and parity checking, in terms of fault coverage as well as area and delay overhead.