Cellular automata basedmulti-bit stuck-at fault diagnosis for resistive memory

This paper presents a group-based dynamic stuck-at fault diagnosis scheme intended for resistive randomaccess memory(ReRAM).Traditional static random-access memory,dynamic random-access memory,NAND,and NOR flash memory are limited by their scalability,power,package density,and so forth.Next-generation memory types like ReRAMs are considered to have various advantages such as high package density,non-volatility,scalability,and low power consumption,but cell reliability has been a problem.Unreliable memory operation is caused by permanent stuck-at faults due to extensive use of write-or memory-intensive workloads.An increased number of stuck-at faults also prematurely limit chip lifetime.Therefore,a cellular automaton(CA)based dynamic stuck-at fault-tolerant design is proposed here to combat unreliable cell functioning and variable cell lifetime issues.A scalable,block-level fault diagnosis and recovery scheme is introduced to ensure readable data despite multi-bit stuck-at faults.The scheme is a novel approach because its goal is to remove all the restrictions on the number and nature of stuck-at faults in general fault conditions.The proposed scheme is based on Wolfram’s null boundary and periodic boundary CA theory.Various special classes of CAs are introduced for 100%fault tolerance:single-lengthcycle single-attractor cellular automata(SACAs),single-length-cycle two-attractor cellular automata(TACAs),and single-length-cycle multiple-attractor cellular automata(MACAs).The target micro-architectural unit is designed with optimal space overhead.