Improved Vertex Coloring With NbO<i>ₓ</i> Memristor-Based Oscillatory Networks

Weiher, Martin; Herzig, Melanie; Tetzlaff, Ronald; Ascoli, Alon; Mikolajick, Thomas; Slesazeck, Stefan

doi:10.1109/tcsi.2021.3061973

Cited by 21 publications

(19 citation statements)

References 31 publications

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“…While significant efforts have been underway in memristor development, there are obvious downfalls to the memristors of today including a high error rate and a low average bit lifespan. These are especially troublesome as emerging types of neuromorphic computing elements rely on the unique characteristics of memristors to mimic the spike timing and continuously variable weights of neurons in our human brains [3][4][5]. The memristive capabilities of phase change materials such as the metal insulator transitional VO 2 and V 2 O 3 are prime candidates for this next generation [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

N+ Irradiation and Substrate-Induced Variability in the Metamagnetic Phase Transition of FeRh Films

et al. 2021

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Metamagnetic FeRh has been the focus of numerous studies for its highly unique antiferromagnetic (AF) to ferromagnetic (FM) metamagnetic transition. While this phase transition usually occurs above room temperature (often Tc > 400 K), both ion irradiation and strained epitaxial growth have been used to bring it to applicable temperatures. Nevertheless, cross sample variability is pervasive in these studies. Here we explore the optical and magnetic properties of 35 nm thick FeRh grown by magnetron sputter deposition simultaneously on two different single crystal substrates: epitaxially on MgO (001) and highly strained with large lattice mismatch on Al2O3 (1000). We then irradiate the epitaxial film with 5 keV N+ ions to introduce disorder (and to a lesser extent, modify chemical composition) without effecting the surface morphology. We find that the phase-transitional properties of both films are strikingly different due to the large lattice mismatch, despite being grown in tandem with nominally identical growth conditions including Fe/Rh stoichiometry, pressure, and temperature. We observe that N+ implantation lowers Tc by ~60 K, yielding a sample with nominally the same transition temperature as the non-epitaxial film on sapphire, yet with a significantly increased magnetic moment, a larger magnetization change and a more abrupt transition profile. We attribute these differences to the Volmer-Weber type growth mode induced by the sapphire substrate and the resulting rougher surface morphology.

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Section: Introductionmentioning

confidence: 99%

N+ Irradiation and Substrate-Induced Variability in the Metamagnetic Phase Transition of FeRh Films

et al. 2021

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“…Since the potassium and sodium ion channels in biological axon membranes (Hodgkin and Huxley, 1952) are locally active memristors (Chua et al, 2012), which provide an essential contribution for the emergence of the all-ornone neuronal spiking behavior, it is clear that solid-state resistance switching memories, which admit a negative smallsignal resistance over a range of operating points, which, as explained in this manuscript, constitutes a signature for their capability to enter the LA domain, will play a major role for the development of basic electronic building blocks of novel biomimetic neuromorphic networks. There have already been a few promising attempts to adopt these kinds of memristor physical realizations (Pickett and Williams, 2012) for the electronic implementation of biological neurons, the so-called neuronal memristors, or neuristors for short Yi et al, 2018), which have been further combined through various coupling arrangements to form memristive cellular automata endowed with computational universality , and memristive cellular neural networks (M-CNNs), which, supporting the emergence of dynamic patterns (Weiher et al, 2019;Demirkol et al, 2021), may be employed to solve complex non-deterministic polynomial-time (NP)-hard optimization problems, such as the challenging task of coloring the vertices of an undirected graph (Weiher et al, 2021). In this article, we employed powerful techniques from non-linear circuit (Chua, 1987) and system (Ascoli et al, 2019;Corinto et al, 2020) theory as well as rigorous concepts from the theory of complexity to gain a thorough understanding of the non-linear dynamics of a locally active memristive microstructure from NaMLab.…”

Section: Discussionmentioning

confidence: 99%

“…Superimposing a small-signal on top of the DC operating point, the locally active memristor may operate similarly as a MOS transistor biased in the saturation region, amplifying the local fluctuations at the expense of some DC power supply. Besides opening up the opportunity to design transistor-less small-signal amplification circuits as well as oscillatory networks, in which the emergence of spatiotemporal phenomena (Weiher et al, 2019) may be exploited to solve complex optimization problems (Weiher et al, 2021), the adoption of locally active memristors in electronics may also allow an accurate reproduction of the non-linear dynamics of potassium and sodium ion channels in innovative 35 It is instructive to observe that even the ion channels in the human heart (Zhang et al, 2020) are volatile locally active memristors. neuromorphic hardware .…”

Section: Discussionmentioning

confidence: 99%

On Local Activity and Edge of Chaos in a NaMLab Memristor

et al. 2021

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Local activity is the capability of a system to amplify infinitesimal fluctuations in energy. Complex phenomena, including the generation of action potentials in neuronal axon membranes, may never emerge in an open system unless some of its constitutive elements operate in a locally active regime. As a result, the recent discovery of solid-state volatile memory devices, which, biased through appropriate DC sources, may enter a local activity domain, and, most importantly, the associated stable yet excitable sub-domain, referred to as edge of chaos, which is where the seed of complexity is actually planted, is of great appeal to the neuromorphic engineering community. This paper applies fundamentals from the theory of local activity to an accurate model of a niobium oxide volatile resistance switching memory to derive the conditions necessary to bias the device in the local activity regime. This allows to partition the entire design parameter space into three domains, where the threshold switch is locally passive (LP), locally active but unstable, and both locally active and stable, respectively. The final part of the article is devoted to point out the extent by which the response of the volatile memristor to quasi-static excitations may differ from its dynamics under DC stress. Reporting experimental measurements, which validate the theoretical predictions, this work clearly demonstrates how invaluable is non-linear system theory for the acquirement of a comprehensive picture of the dynamics of highly non-linear devices, which is an essential prerequisite for a conscious and systematic approach to the design of robust neuromorphic electronics. Given that, as recently proved, the potassium and sodium ion channels in biological axon membranes are locally active memristors, the physical realization of novel artificial neural networks, capable to reproduce the functionalities of the human brain more closely than state-of-the-art purely CMOS hardware architectures, should not leave aside the adoption of resistance switching memories, which, under the appropriate provision of energy, are capable to amplify the small signal, such as the niobium dioxide micro-scale device from NaMLab, chosen as object of theoretical and experimental study in this work.

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“…CMOS scaling has further fueled the speed and number of such units that can be packed on a chip to increase functionality and reduce processing times. However, there emerges a class of problems that are either data intensive (e.g., classification) or require stochastic functionality (e.g., optimization) or both. − These often tend to be NP-hard in complexity on the traditional digital von-Neumann computing architectures. ,, Nonetheless, the demand for frequent solutions to graphical optimization problems like the Traveling Salesman (cab pooling services and 5G beam tracking), Max-Cut (VLSI design and layout automation), or Vertex Coloring (scheduling and routing) is on the rise especially at the edge. − Efficient architectures like in-memory computing and strategies to accelerate them are thus of critical importance in such resource constrained environments.…”

Section: Introductionmentioning

confidence: 99%

Highly Deterministic One-Shot Set–Reset Programming Scheme in PCMO Resistive Random-Access Memory

Phadke

Saraswat

Ganguly

2022

ACS Appl. Electron. Mater.

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Resistive random-access memory (RRAM) devices are very versatile with applications ranging from digital nonvolatile memories to analog synapses and integrate-fire neurons. Recently, RRAM based stochastic neurons have also been proposed for optimization networks that solve NP-hard problems. These applications rely on reliably writing a given conductance state repeatedly. A Pr1–x Ca x MnO3 (PCMO) based RRAM device is a nonfilamentary, bulk switching RRAM which demonstrates low device-to-device variations compared to filamentary RRAMs. However, a low complexity programming scheme to demonstrate low cycle-to-cycle variations (C2CV) as well is needed. In this work, we propose a one-shot Set (initialize) and Reset (program) scheme to experimentally demonstrate low C2CV (<15%) for multiple devices. Compared to one-shot programming on a filamentary device, there is a 2–4× increment in the number of levels that can be stored per device using PCMO RRAM. Further, one-shot programming in PCMO RRAM leads to a 35× (10×) reduction in the number of pulses for 3 (2) bits per device, respectively. This greatly simplifies the memory controller design for these devices compared to any iterative write-verify schemes. This scheme gives a further insight into the self-heating limited Set operation controlled by a series resistor while reinforcing the analog and precise nature of the Reset operation. We studied the impact of the C2CV in programming RRAM-based stochastic neurons on the Max-Cut optimization problem using Boltzmann machines. PCMO RRAM combined with the one-shot programming scheme emerges as the clear choice for a well-controlled RRAM device with minimal peripheral complexity.

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Improved Vertex Coloring With NbOₓ Memristor-Based Oscillatory Networks

Cited by 21 publications

References 31 publications

N+ Irradiation and Substrate-Induced Variability in the Metamagnetic Phase Transition of FeRh Films

N+ Irradiation and Substrate-Induced Variability in the Metamagnetic Phase Transition of FeRh Films

On Local Activity and Edge of Chaos in a NaMLab Memristor

Highly Deterministic One-Shot Set–Reset Programming Scheme in PCMO Resistive Random-Access Memory

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