Minimizing energy dissipation during programming of resistive switching memory devices using their dynamical attractor states

Abstract Under certain conditions, applying a sequence of voltage pulses of alternating polarities across a resistive switching memory device induces a finite number of fixed-point attractors in its time-averaged dynamics, known as dynamical attractors. Remarkably, dynamical attractors can be used to program analog values into the device state without supervision. Because different pulse sequences can produce the same trajectory solution for the state in the phase space, there is strong potential for optimization, particularly regarding the energy cost of the programming phase, which this study addresses. The proposed theory-based energy minimization strategy is applied to the voltage threshold adaptive memristor model, which is known for its predictive capability and adaptability in fitting a large number of resistive switching memory devices. The optimization design crafts ad-hoc pulse sequences that minimize the energy required to program the device into a desired dynamical attractor. The theoretical approach is also extended to cover situations where a fast programming scheme should be adopted to serve time-critical electronics applications.