arXiv subjects

R. Stanley Williams

Publications and source records attributed to R. Stanley Williams.

At least 19 recordsLinked to original sources

arXiv2021

Improved Hopfield Network Optimization using Manufacturable Three-terminal Electronic Synapses

We describe via simulation novel optimization algorithms for a Hopfield neural network constructed using manufacturable three-terminal Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) synaptic devices. We first present a computationally-light, memristor-based, highly accurate compact model for the SONOS. Using the compact model, we describe techniques of simulated annealing in Hopfield networks by exploiting imperfect problem definitions, current leakage, and the continuous tunability of the SONOS to enable transient chaotic group dynamics. We project improvements in energy consumption and latency for optimization relative to the best CPUs and GPUs by at least 4 orders of magnitude, and also exceeding the best projected memristor-based hardware; along with a 100-fold increase in error-resilient hardware size (i.e., problem size).

cond-mat.mtrl-sci↗

arXiv2020

Size scaling, dynamics, and electro-thermal bifurcation of VO2 Mott oscillators

Traditional electronic devices are well-known to improve in speed and energy-efficiency as their dimensions are reduced to the nanoscale. However, this scaling behavior remains unclear for nonlinear dynamical circuit elements, such as Mott neuron-like spiking oscillators, which are of interest for bio-inspired computing. Here we show that shrinking micrometer-sized VO2 oscillators to sub-100 nm effective sizes, achieved using a nanogap cut in a metallic carbon nanotube (CNT) electrode, does not guarantee faster spiking. However, an additional heat source such as Joule heating from the CNT, in combination with small size and heat capacity (defined by the narrow volume of VO2 whose insulator-metal transition is triggered by the CNT), can increase the spiking frequency by ~1000x due to an electro-thermal bifurcation in the nonlinear dynamics. These results demonstrate that nonlinear dynamical switches operate in a complex phase space which can be controlled by careful electro-thermal design, offering new tuning parameters for designing future biomimetic electronics.

cond-mat.mtrl-sci↗

arXiv2019

Thermodynamic Computing

The hardware and software foundations laid in the first half of the 20th Century enabled the computing technologies that have transformed the world, but these foundations are now under siege. The current computing paradigm, which is the foundation of much of the current standards of living that we now enjoy, faces fundamental limitations that are evident from several perspectives. In terms of hardware, devices have become so small that we are struggling to eliminate the effects of thermodynamic fluctuations, which are unavoidable at the nanometer scale. In terms of software, our ability to imagine and program effective computational abstractions and implementations are clearly challenged in complex domains. In terms of systems, currently five percent of the power generated in the US is used to run computing systems - this astonishing figure is neither ecologically sustainable nor economically scalable. Economically, the cost of building next-generation semiconductor fabrication plants has soared past $10 billion. All of these difficulties - device scaling, software complexity, adaptability, energy consumption, and fabrication economics - indicate that the current computing paradigm has matured and that continued improvements along this path will be limited. If technological progress is to continue and corresponding social and economic benefits are to continue to accrue, computing must become much more capable, energy efficient, and affordable. We propose that progress in computing can continue under a united, physically grounded, computational paradigm centered on thermodynamics. Herein we propose a research agenda to extend these thermodynamic foundations into complex, non-equilibrium, self-organizing systems and apply them holistically to future computing systems that will harness nature's innate computational capacity. We call this type of computing "Thermodynamic Computing" or TC.

cs.CY↗

arXiv2019

Fast Spiking of a Mott VO2-Carbon Nanotube Composite Device

The recent surge of interest in brain-inspired computing and power-efficient electronics has dramatically bolstered development of computation and communication using neuron-like spiking signals. Devices that can produce rapid and energy-efficient spiking could significantly advance these applications. Here we demonstrate DC-current or voltage-driven periodic spiking with sub-20 ns pulse widths from a single device composed of a thin VO2 film with a metallic carbon nanotube as a nanoscale heater. Compared with VO2-only devices, adding the nanotube heater dramatically decreases the transient duration and pulse energy, and increases the spiking frequency, by up to three orders of magnitude. This is caused by heating and cooling of the VO2 across its insulator-metal transition being localized to a nanoscale conduction channel in an otherwise bulk medium. This result provides an important component of energy-efficient neuromorphic computing systems, and a lithography-free technique for power-scaling of electronic devices that operate via bulk mechanisms.

physics.app-ph↗

arXiv2019

PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference

Memristor crossbars are circuits capable of performing analog matrix-vector multiplications, overcoming the fundamental energy efficiency limitations of digital logic. They have been shown to be effective in special-purpose accelerators for a limited set of neural network applications. We present the Programmable Ultra-efficient Memristor-based Accelerator (PUMA) which enhances memristor crossbars with general purpose execution units to enable the acceleration of a wide variety of Machine Learning (ML) inference workloads. PUMA's microarchitecture techniques exposed through a specialized Instruction Set Architecture (ISA) retain the efficiency of in-memory computing and analog circuitry, without compromising programmability. We also present the PUMA compiler which translates high-level code to PUMA ISA. The compiler partitions the computational graph and optimizes instruction scheduling and register allocation to generate code for large and complex workloads to run on thousands of spatial cores. We have developed a detailed architecture simulator that incorporates the functionality, timing, and power models of PUMA's components to evaluate performance and energy consumption. A PUMA accelerator running at 1 GHz can reach area and power efficiency of $577~GOPS/s/mm^2$ and $837~GOPS/s/W$, respectively. Our evaluation of diverse ML applications from image recognition, machine translation, and language modelling (5M-800M synapses) shows that PUMA achieves up to $2,446\times$ energy and $66\times$ latency improvement for inference compared to state-of-the-art GPUs. Compared to an application-specific memristor-based accelerator, PUMA incurs small energy overheads at similar inference latency and added programmability.

cs.ET↗

arXiv2018

Long short-term memory networks in memristor crossbars

Recent breakthroughs in recurrent deep neural networks with long short-term memory (LSTM) units has led to major advances in artificial intelligence. State-of-the-art LSTM models with significantly increased complexity and a large number of parameters, however, have a bottleneck in computing power resulting from limited memory capacity and data communication bandwidth. Here we demonstrate experimentally that LSTM can be implemented with a memristor crossbar, which has a small circuit footprint to store a large number of parameters and in-memory computing capability that circumvents the 'von Neumann bottleneck'. We illustrate the capability of our system by solving real-world problems in regression and classification, which shows that memristor LSTM is a promising low-power and low-latency hardware platform for edge inference.

cs.ET↗

arXiv2017

Challenges to Keeping the Computer Industry Centered in the US

It is undeniable that the worldwide computer industry's center is the US, specifically in Silicon Valley. Much of the reason for the success of Silicon Valley had to do with Moore's Law: the observation by Intel co-founder Gordon Moore that the number of transistors on a microchip doubled at a rate of approximately every two years. According to the International Technology Roadmap for Semiconductors, Moore's Law will end in 2021. How can we rethink computing technology to restart the historic explosive performance growth? Since 2012, the IEEE Rebooting Computing Initiative (IEEE RCI) has been working with industry and the US government to find new computing approaches to answer this question. In parallel, the CCC has held a number of workshops addressing similar questions. This whitepaper summarizes some of the IEEE RCI and CCC findings. The challenge for the US is to lead this new era of computing. Our international competitors are not sitting still: China has invested significantly in a variety of approaches such as neuromorphic computing, chip fabrication facilities, computer architecture, and high-performance simulation and data analytics computing, for example. We must act now, otherwise, the center of the computer industry will move from Silicon Valley and likely move off shore entirely.

cs.CY↗

arXiv2017

Oxygen migration during resistance switching and failure of hafnium oxide memristors

While the recent establishment of the role of thermophoresis/diffusion-driven oxygen migration during resistance switching in metal oxide memristors provided critical insights required for memristor modeling, extended investigations of the role of oxygen migration during ageing and failure remain to be detailed. Such detailing will enable failure-tolerant design, which can lead to enhanced performance of memristor-based next-generation storage-class memory. Here we directly observed lateral oxygen migration using in-situ synchrotron x-ray absorption spectromicroscopy of HfOx memristors during initial resistance switching, wear over millions of switching cycles, and eventual failure, through which we determined potential physical causes of failure. Using this information, we reengineered devices to mitigate three failure mechanisms, and demonstrated an improvement in endurance of about three orders of magnitude.

cond-mat.mtrl-sci↗

arXiv2017

Spatially uniform resistance switching of low current, high endurance titanium-niobium-oxide memristors

We analyzed micrometer-scale titanium-niobium-oxide prototype memristors, which exhibited low write-power (<3 μW) and energy (<200 fJ/bit/μm2), low read-power (~nW), and high endurance (>millions of cycles). To understand their physico-chemical operating mechanisms, we performed in-operando synchrotron x-ray transmission nanoscale spectromicroscopy using an ultra-sensitive time-multiplexed technique. We observed only spatially uniform material changes during cell operation, in sharp contrast to the frequently detected formation of a localized conduction channel in transition-metal-oxide memristors. We also associated the response of assigned spectral features distinctly to non-volatile storage (resistance change) and writing of information (application of voltage and Joule heating). These results provide critical insights into high-performance memristors that will aid in device design, scaling and predictive circuit-modeling, all of which are essential for the widespread deployment of successful memristor applications.

cond-mat.mtrl-sci↗

arXiv2017

Conduction Channel Formation and Dissolution Due to Oxygen Thermophoresis/Diffusion in Hafnium Oxide Memristors

Transition metal oxide memristors, or resistive random-access memory (RRAM) switches, are under intense development for storage-class memory because of their favorable operating power, endurance, speed, and density. Their commercial deployment critically depends on predictive compact models based on understanding nanoscale physico-chemical forces, which remains elusive and controversial owing to the difficulties in directly observing atomic motions during resistive switching, Here, using scanning transmission synchrotron x-ray spectromicroscopy to study in-situ switching of hafnium oxide memristors, we directly observed the formation of a localized oxygen-deficiency-derived conductive channel surrounded by a low-conductivity ring of excess oxygen. Subsequent thermal annealing homogenized the segregated oxygen, resetting the cells towards their as-grown resistance state. We show that the formation and dissolution of the conduction channel are successfully modeled by radial thermophoresis and Fick diffusion of oxygen atoms driven by Joule heating. This confirmation and quantification of two opposing nanoscale radial forces that affect bipolar memristor switching are important components for any future physics-based compact model for the electronic switching of these devices.

cond-mat.mtrl-sci↗

arXiv2016

The phase transition in VO2 probed using x-ray, visible and infrared radiations

Vanadium dioxide (VO2) is a model system that has been used to understand closely-occurring multiband electronic (Mott) and structural (Peierls) transitions for over half a century due to continued scientific and technological interests. Among the many techniques used to study VO2, the most frequently used involve electromagnetic radiation as a probe. Understanding of the distinct physical information provided by different probing radiations is incomplete, mostly owing to the complicated nature of the phase transitions. Here we use transmission of spatially averaged infrared (λ=1500 nm) and visible (λ=500 nm) radiations followed by spectroscopy and nanoscale imaging using x-rays (λ=2.25-2.38 nm) to probe the same VO2 sample while controlling the ambient temperature across its hysteretic phase transitions and monitoring its electrical resistance. We directly observed nanoscale puddles of distinct electronic and structural compositions during the transition. The two main results are that, during both heating and cooling, the transition of infrared and visible transmission occur at significantly lower temperatures than the Mott transition; and the electronic (Mott) transition occurs before the structural (Peierls) transition in temperature. We use our data to provide insights into possible microphysical origins of the different transition characteristics. We highlight that it is important to understand these effects because small changes in the nature of the probe can yield quantitatively, and even qualitatively, different results when applied to a non-trivial multiband phase transition. Our results guide more judicious use of probe type and interpretation of the resulting data.

cond-mat.str-el↗

arXiv2016

Direct Observation of Localized Radial Oxygen Migration in Functioning Tantalum Oxide Memristors

Oxygen migration in tantalum oxide, a promising next-generation storage material, is studied using in-operando x-ray absorption spectromicroscopy and is used to microphysically describe accelerated evolution of conduction channel and device failure. The resulting ring-like patterns of oxygen concentration are modeled using thermophoretic forces and Fick diffusion, establishing the critical role of temperature-activated oxygen migration that has been under question lately.

cond-mat.mtrl-sci↗

arXiv2015

Sequential Electronic and Structural Transitions in VO2 Observed Using X-ray Absorption Spectromicroscopy

The popular dual electronic (Mott) and structural (Peierls) transitions in VO2 are explored using x-ray absorption spectromicroscopy with high spatial and spectral resolutions. It is found that during both heating and cooling, the electronic transition always precedes the structural Peierls transition. Between the two transitions, there are intermediate states that are spectrally isolated here.

cond-mat.str-el↗

arXiv2015

Local Temperature Redistribution and Structural Transition During Joule-Heating-Driven Conductance Switching in VO2

Joule-heating induced conductance-switching is studied in VO2, a Mott insulator. Complementary in-situ techniques including optical characterization, blackbody microscopy, scanning transmission x-ray microscopy (STXM) and numerical simulations are used. Abrupt redistribution in local temperature is shown to occur upon conductance-switching along with a structural phase transition, at the same current.

cond-mat.mtrl-sci↗

arXiv2015

In-operando synchronous time-multiplexed O K-edge x-ray absorption spectromicroscopy of functioning tantalum oxide memristors

Memristors are receiving keen interest because of their potential varied applications and promising large-scale information storage capabilities. Tantalum oxide is a memristive material that has shown promise for high-performance nonvolatile computer memory. The microphysics has been elusive because of the small scale and subtle physical changes that accompany conductance switching. In this study, we probed the atomic composition, local chemistry and electronic structure of functioning tantalum oxide memristors through spatially mapped O K-edge x-ray absorption. We developed a time-multiplexed spectromicroscopy technique to enhance the weak and possibly localized oxide modifications with spatial and spectral resolutions of <30 nm and 70 meV, respectively. During the initial stages of conductance switching of a micrometer sized crosspoint device, the spectral changes were uniform within the spatial resolution of our technique. When the device was further driven with millions of high voltage-pulse cycles, we observed lateral motion and separation of ~100 nm-scale agglomerates of both oxygen interstitials and vacancies. We also demonstrate a unique capability of this technique by identifying the relaxation behavior in the material during electrical stimuli by identifying electric field driven changes with varying pulse widths. In addition, we show that changes to the material can be localized to a spatial region by modifying its topography or uniformity, as against spatially uniform changes observed here during memristive switching. The goal of this report is to introduce the capability of time-multiplexed x-ray spectromicroscopy in studying weak-signal transitions in inhomogeneous media through the example of the operation and temporal evolution of a memristor.

cond-mat.mtrl-sci↗

arXiv2011

Current-Controlled Negative Differential Resistance due to Joule Heating in TiO2

We show that Joule heating causes current-controlled negative differential resistance (CC-NDR) in TiO2 by constructing an analytical model of the voltage-current V(I) characteristic based on polaronic transport for Ohm's Law and Newton's Law of Cooling, and fitting this model to experimental data. This threshold switching is the 'soft breakdown' observed during electroforming of TiO2 and other transition-metal-oxide based memristors, as well as a precursor to 'ON' or 'SET' switching of unipolar memristors from their high to their low resistance states. The shape of the V(I) curve is a sensitive indicator of the nature of the polaronic conduction.

cond-mat.mes-hall↗

arXiv2011

Molecular dynamics simulations of oxide memristors: crystal field effects

We present molecular-dynamic simulations of memory resistors (memristors) including the crystal field effects on mobile ionic species such as oxygen vacancies appearing during operation of the device. Vacancy distributions show different patterns depending on the ratio of a spatial period of the crystal field to a characteristic radius of the vacancy-vacancy interaction. There are signatures of the orientational order and of spatial voids in the vacancy distributions for some crystal field potentials. The crystal field stabilizes the patterns after they are formed, resulting in a non-volatile switching of the simulated devices.

cond-mat.mtrl-sci↗

arXiv2010

Molecular dynamics simulations of oxide memristors: thermal effects

We have extended our recent molecular-dynamic simulations of memristors to include the effect of thermal inhomogeneities on mobile ionic species appearing during operation of the device. Simulations show a competition between an attractive short-ranged interaction between oxygen vacancies and an enhanced local temperature in creating/destroying the conducting oxygen channels. Such a competition would strongly affect the performance of the memristive devices.

cond-mat.mes-hall↗