Recently, the leakage power consumption of Internet of Things (IoT) devices has become a main issue to be tackled, due to the fact that the scaling of process technology increases the leakage current in the IoT devices having limited battery capacity, resulting in the reduction of battery lifetime. The most effective method to extend the battery lifetime is to shut-off the device during standby mode. For this reason, spin-transfer-torque magnetic-tunnel-junction (STT-MTJ) based nonvolatile flip-flop (NVFF) is being considered as a strong candidate to store the computing data. Since there is a risk that the MTJ resistance may change during the read operation (i.e., the read disturbance problem), NVFF should consider the read disturbance problem to satisfy reliable data restoration. To date, several NVFFs have been proposed. Even though they satisfy the target restore yield of 4σ, most of them do not take the read disturbance into account. Furthermore, several recently proposed NVFFs which focus on the offset-cancellation technique to improve the restore yield have obvious limitation with decreasing the supply voltage (VDD), because the offset-cancellation technique uses switch operation in the critical path that can exacerbate the restore yield in the near/sub-threshold region. In this regard, this paper analyzes state-of-the-art STT-MTJ based NVFFs with respect to the voltage region and provides insight that a simple circuit having no offset-cancellation technique could achieve a better restore yield in the near/sub-threshold voltage region. Monte–Carlo HSPICE simulation results, using industry-compatible 28 nm model parameters, show that in case of VDD of 0.6 V, complex NVFF circuits having offset tolerance characteristic have a better restore yield, whereas in case of VDD of 0.4 V with sizing up strategy, a simple NVFF circuit having no offset tolerance characteristic has a better restore yield.
Novel MTJ-Based Sensing Inverter Variation Tolerant Nonvolatile Flip-Flop in the Near-Threshold Voltage Region
