High precision analogue memristor state tuning

Abstract

A report is presented on the operation of an analogue programming circuit for accurately setting the state of a memristor. The circuit exploits the dynamic modulation of resistance under a constant DC bias while real-time measurements of the memristance are performed using an AC signal. The circuit employs feedback for converging the state of a device at any required level within a decade. This allows the memristor to act as an analogue potentiometer, with its resistance corresponding to an input analogue voltage. This implementation was tested with the HP memristor model revealing an accuracy of less than 0.4% (8 bit precision) in relation to the full dynamic range.Introduction: The memristor is a description of a basic phenomenon of nature [1] that was postulated as the fourth missing element by Chua [2] and has attracted significant research interest after HP identified this phenomenon in nanoscale resistive-RAM [3]. Its unconventional properties, non-volatile memory that depends upon the biasing history and nonlinearity, enable the development of new circuit architectures that can facilitate low precision analogue computation [4], neuromorphic circuits [5] and resistive memory [6].In all cases, programming a memristor with increased accuracy is therefore essential. Several circuits have been proposed for this reason that can be divided into two main categories: (i) utilising distinct width and amplitude pulses to read, write and reset a device to an intermediate state [7,8], and (ii) using one or several linear resistors as references in order for the memristance to 'latch' onto the reference resistor [9,10]. The drawback of the first method is associated with external processing needed to calculate the pulse timings, for compensating the highly nonlinear dynamics of the device, while the latter scenario is typically avoided as it is component-hungry, due to the reference resistors needed for setting the programming precision. In this Letter, we propose an analogue approach to memristor programming that does not suffer from the limitations described above, and most importantly, can provide a linear relationship between an analogue input voltage and the final programmed value of memristance. Our approach was evaluated with SPICE simulations and we demonstrate that programming the device within 8 bit precision is possible.

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“…It constitutes of memristors (Ag-Si) with conductivity g ij , interconnecting two sets of metal bars (i th horizontal bar and j th in-plane bar). High precision, multi-level write techniques for isolated memristors have been proposed and demonstrated in literatures that can achieve more than 8-bit write-accuracy [9,10]. In a cross-bar array, consisting of large number of memristors, write voltage applied across two cross connected bars for programming the interconnecting memristor also results in sneak current paths through neighboring devices.…”

“…More importantly, devices that can facilitate direct 'in-memory' processing, may be highly attractive for such memory intensive computing. Several device solutions have been proposed for fabricating nano-scale programmable resistive elements, generally categorized under the term 'memristor' [9][10][11][12][13][14][15][16][17]. Of special interest are those which are amenable to integration with state of the art CMOS technology, like memristors based on Ag-Si filaments [14][15][16].…”

“…Of special interest are those which are amenable to integration with state of the art CMOS technology, like memristors based on Ag-Si filaments [14][15][16]. Such devices can be integrated into metallic cross-bars to obtain high density resistive cross-bar networks (RCN) [9][10][11][12][13][14][15][16]. Continuous range of resistance values obtainable in these devices can facilitate the design of multilevel, non-volatile memory [9][10][11].…”

“…Such devices can be integrated into metallic cross-bars to obtain high density resistive cross-bar networks (RCN) [9][10][11][12][13][14][15][16]. Continuous range of resistance values obtainable in these devices can facilitate the design of multilevel, non-volatile memory [9][10][11]. The RCN technology has led to interesting possibilities of combining memory with computation [9][10][11][12][13].…”

“…Continuous range of resistance values obtainable in these devices can facilitate the design of multilevel, non-volatile memory [9][10][11]. The RCN technology has led to interesting possibilities of combining memory with computation [9][10][11][12][13]. RCN can be highly suitable for large number of non-Boolean computing applications that involve pattern-matching [13,19].…”