Minimizing energy dissipation during programming of resistive switching memory devices using their dynamical attractor states
Valeriy A. Slipko, Alon Ascoli, Fernando Corinto, Yuriy V. Pershin

TL;DR
This paper introduces a theory-based method to optimize voltage pulse sequences for resistive memory devices, minimizing energy consumption during programming by leveraging dynamical attractor states.
Contribution
It presents a novel energy minimization strategy for programming resistive memory devices using dynamical attractors, applicable to the VTEAM model.
Findings
Optimized pulse sequences reduce energy consumption.
Method applicable to time-critical programming scenarios.
Demonstrated on the VTEAM memristor model.
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 (VTEAM) 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…
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Taxonomy
TopicsAdvanced Memory and Neural Computing · Neural Networks Stability and Synchronization · Ferroelectric and Negative Capacitance Devices
