Memristors are nano-devices, which, in some of their physical realisations, feature multiple operating modes, allowing data to be alternatively sensed, stored, or processed. Their multifunctionality, which resembles the operating principles of neural structures in the brain, in conjunction with the ease of their fabrication, which is typically carried out on top of underlying CMOS circuitry, at the regularly-spaced spaced crossings of crossbar matrices, composed of two vertically-adjacent and perpendicular sets of parallel metal lines, makes their use in integrated circuit design ideally suitable for enhancing the performance of stateof- the-art computing machines without the need to shrink the sizes of CMOS transistors any further. Given the extraordinary opportunities, which memristors open up in the field of Artificial Intelligence, gaining a deep understanding of their inherentlynonlinear dynamics is of primary importance. Fading memory is the capability of a system to display a unique steady state under a stimulus from a given class. Fading memory effects in a memristive medium were first discovered in 2016 through a comprehensive experimental and theoretical investigation of the switching dynamics of a TaOx ReRAM cell. Recently, a bifurcation study of a predictive model of the same nanostructure revealed how it may also exhibit bi-stability under suitable AC periodic excitation. Bi-stability is essentially a local form of fading memory. This paper gains a deeper insight into the local fading memory properties of the TaOx ReRAM cell, demonstrating how the existence domain for its memory state may be in fact partitioned in a tuneable number of basins of attraction, each of which includes all the initial conditions, from which the memristor would settle into one of the admissible locally-stable oscillatory steady states.

Local Fading Memory Effects in a Tantalum Oxide ReRAM Cell from Hewlett Packard Labs / Ascoli, A; Schmitt, N.; Messaris, I.; Demirkol, A. S.; Tetzlaff, R.; Strachan, J. P.; Chua, L. O.. - ELETTRONICO. - (2023), pp. 971-976. (Intervento presentato al convegno IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) tenutosi a Milano, Italy nel 25-27 October 2023) [10.1109/METROXRAINE58569.2023.10405685].

Local Fading Memory Effects in a Tantalum Oxide ReRAM Cell from Hewlett Packard Labs

Ascoli, A;
2023

Abstract

Memristors are nano-devices, which, in some of their physical realisations, feature multiple operating modes, allowing data to be alternatively sensed, stored, or processed. Their multifunctionality, which resembles the operating principles of neural structures in the brain, in conjunction with the ease of their fabrication, which is typically carried out on top of underlying CMOS circuitry, at the regularly-spaced spaced crossings of crossbar matrices, composed of two vertically-adjacent and perpendicular sets of parallel metal lines, makes their use in integrated circuit design ideally suitable for enhancing the performance of stateof- the-art computing machines without the need to shrink the sizes of CMOS transistors any further. Given the extraordinary opportunities, which memristors open up in the field of Artificial Intelligence, gaining a deep understanding of their inherentlynonlinear dynamics is of primary importance. Fading memory is the capability of a system to display a unique steady state under a stimulus from a given class. Fading memory effects in a memristive medium were first discovered in 2016 through a comprehensive experimental and theoretical investigation of the switching dynamics of a TaOx ReRAM cell. Recently, a bifurcation study of a predictive model of the same nanostructure revealed how it may also exhibit bi-stability under suitable AC periodic excitation. Bi-stability is essentially a local form of fading memory. This paper gains a deeper insight into the local fading memory properties of the TaOx ReRAM cell, demonstrating how the existence domain for its memory state may be in fact partitioned in a tuneable number of basins of attraction, each of which includes all the initial conditions, from which the memristor would settle into one of the admissible locally-stable oscillatory steady states.
2023
979-8-3503-0080-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2985859