The Role of the Programming Trajectory in the Power Dissipation Dynamics and Energy Consumption of Memristive Devices

Tuning the conductance of a memristive device is a process that requires energy and involves power dissipation. In this letter, the role the memory state programming strategy plays in this connection is investigated. To this end, the device model equations representing the electron transport and metal ion/oxygen vacancy displacement caused by the application of an external signal must be solved consistently. However, if instead of considering the applied voltage as the model input, a memory state trajectory is assumed, the model equations can be decoupled allowing an analytic description of the problem. In order to accomplish this objective a more accurate version of the dynamic memdiode model is used which incorporates additional physical considerations in the characteristic switching times. It is demonstrated that alternative trajectories (concave, convex, and sigmoidal) lead to a variety of energy consumption-maximum dissipated power relationships highlighting the key role played by the selected programming strategy. This kind of study contributes to the basic understanding of the writing process of memristors (synaptic weight assignment in neural networks) shedding light on the associated electrical effects.