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A model is presented that reproduces spiking and bursting behavior of known types of cortical neurons. The model combines the biologically plausibility of Hodgkin-Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using this model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC.
Despite the overwhelming effort to improve the efficacy of resistive random access memory (RRAM), the underlying physics governing RRAM operation have proven elusive. A survey of the recent literature almost universally indicates that the remaining glaring issues center around variability as well as endurance. The initial filamentary “forming” process is often linked to these problems. This work details our recent efforts to bring the forming process under control and the resulting improvements in RRAM viability in hafnia-based devices. We track the forming process via a “forming energy” metric that allows for filament optimization. By removal of all current compliance elements, and their associated parasitics, a targeted forming energy is achieved using ultrashort voltage pulses. By tailoring the forming energy, we show remarkable endurance window control.