Wu Jun-Jie

SPICE modeling of memristors with multilevel resistance states

With CMOS technologies approaching the scaling ceiling, novel memory technologies have thrived in recent years, among which the memristor is a rather promising candidate for future resistive memory (RRAM). Memristors potential to store multiple bits of information as different resistance levels allows its application in multilevel cell (MCL) technology, which can significantly increase the memory capacity. However, most existing memristor models are built for binary or continuous memristance switching. In this paper, we propose the simulation program with integrated circuits emphasis (SPICE) modeling of charge-controlled and flux-controlled memristors with multilevel resistance states based on the memristance versus state map. In our model, the memristance switches abruptly between neighboring resistance states. The proposed model allows users to easily set the number of the resistance levels as parameters, and provides the predictability of resistance switching time if the input current/voltage waveform is given. The functionality of our models has been validated in HSPICE. The models can be used in multilevel RRAM modeling as well as in artificial neural network simulations.

Finding tree symmetries using continuous-time quantum walk

Quantum walk, the quantum counterpart of random walk, is an important model and widely studied to develop new quantum algorithms. This paper studies the relationship between the continuous-time quantum walk and the symmetry of a graph, especially that of a tree. Firstly, we prove in mathematics that the symmetry of a graph is highly related to quantum walk. Secondly, we propose an algorithm based on the continuous-time quantum walk to compute the symmetry of a tree. Our algorithm has better time complexity O(N3) than the current best algorithm. Finally, through testing three types of 10024 trees, we find that the symmetry of a tree can be found with an extremely high efficiency with the help of the continuous-time quantum walk.

Impact of multiplexed reading scheme on nanocrossbar memristor memory's scalability

Nanocrossbar is a potential memory architecture to integrate memristor to achieve large scale and high density memory. However, based on the currently widely-adopted parallel reading scheme, scalability of the nanocrossbar memory is limited, since the overhead of the reading circuits is in proportion with the size of the nanocrossbar component. In this paper, a multiplexed reading scheme is adopted as the foundation of the discussion. Through HSPICE simulation, we reanalyze scalability of the nanocrossbar memristor memory by investigating the impact of various circuit parameters on the output voltage swing as the memory scales to larger size. We find that multiplexed reading maintains sufficient noise margin in large size nanocrossbar memristor memory. In order to improve the scalability of the memory, memristors with nonlinear I—V characteristics and high LRS (low resistive state) resistance should be adopted.

Betweenness-based algorithm for a partition scale-free graph

Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom—up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top—down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.

Analysis and modeling of resistive switching mechanism oriented to fault tolerance of resistive memory based on memristor

With the progress of the semiconductor industry, resistive memories, especially the memristor, have drawn increasing attention. The resistive memory based on memrsitor has not been commercialized mainly because of data error. Currently, there are more studies focused on fault tolerance of resistive memory. This paper studies the resistive switching mechanism which may have time-varying characteristics. Resistive switching mechanism is analyzed and its respective circuit model is established based on the memristor Spice model.

Speeding up the MATLAB complex networks package using graphic processors

The availability of computers and communication networks allows us to gather and analyse data on a far larger scale than previously. At present, it is believed that statistics is a suitable method to analyse networks with millions, or more, of vertices. The MATLAB language, with its mass of statistical functions, is a good choice to rapidly realize an algorithm prototype of complex networks. The performance of the MATLAB codes can be further improved by using graphic processor units (GPU). This paper presents the strategies and performance of the GPU implementation of a complex networks package, and the Jacket toolbox of MATLAB is used. Compared with some commercially available CPU implementations, GPU can achieve a speedup of, on average, 11.3×. The experimental result proves that the GPU platform combined with the MATLAB language is a good combination for complex network research.

Analysis and modeling of resistive switching mechanisms oriented to resistive random-access memory

With the progress of the semiconductor industry, the resistive random-access memory (RAM) has drawn increasing attention. The discovery of the memristor has brought much attention to this study. Research has focused on the resistive switching characteristics of different materials and the analysis of resistive switching mechanisms. We discuss the resistive switching mechanisms of different materials in this paper and analyze the differences of those mechanisms from the view point of circuitry to establish their respective circuit models. Finally, simulations are presented. We give the prospect of using different materials in resistive RAM on account of their resistive switching mechanisms, which are applied to explain their resistive switchings.

SPICE modeling of flux-controlled unipolar memristive devices

Unipolar memristive devices are an important kind of resistive switching devices. However, few circuit models of them have been proposed. In this paper, we propose the SPICE modeling of flux-controlled unipolar memristive devices based on the memristance versus state map. Using our model, the flux thresholds, ON and OFF resistance, and compliance current can easily be set as model parameters. We simulate the model in HSPICE using model parameters abstracted from real devices, and the simulation results show that the proposed model caters to the real device data very well, thus demonstrating that the model is correct. Using the same modeling methodology, the SPICE model of charge-controlled unipolar memristive devices could also be developed. The proposed model could be used to model resistive memory cells, logical gates as well as synapses in artificial neural networks.

Statistical analysis of the temporal single-photon response of superconducting nanowire single photon detection*

A new method to study the transient detection efficiency (DE) and pulse amplitude of superconducting nanowire single photon detectors (SNSPD) during the current recovery process is proposed — statistically analyzing the single photon response under photon illumination with a high repetition rate. The transient DE results match well with the DEs deduced from the static current dependence of DE combined with the waveform of a single-photon detection event. This proves that static measurement results can be used to analyze the transient current recovery process after a detection event. The results are relevant for understanding the current recovery process of SNSPDs after a detection event and for determining the counting rate of SNSPDs.Counting rate is a key parameter of superconducting nanowire single photon detectors (SNSPD) and is determined by the current recovery time of an SNSPD after a detection event. We propose a new method to study the transient detection efficiency (DE) and pulse amplitude during the current recovery process by statistically analyzing the single photon response of an SNSPD under photon illumination with a high repetition rate. The transient DE results match well with the DEs deduced from the static current dependence of DE combined with the waveform of a single-photon detection event. This proves that the static measurement results can be used to analyze the transient current recovery process after a detection event. The results are relevant for understanding the current recovery process of SNSPDs after a detection event and for determining the counting rate of SNSPDs.

Development of MEMS-based micro capacitive tactile probe

In this paper, a micro capacitive sensor with nanometer resolution is presented for ultra-precision measurement of micro components, which is fabricated by the MEMS (micro electromechanical systems) non-silicon technique. Based on the sensor, a micro capacitive tactile probe is constructed by stylus assembly and packaging design for dimension metrology on micro/nano scale, in which a data acquiring system is developed with AD7747. Some measurements of the micro capacitive tactile probe are performed on a nano positioning and measuring machine (NMM). The measurement results show good linearity and hysteresis with a range of 11.6 μm and resolution of better than 5 nm. Hence, the micro capacitive tactile probe can be integrated on NMM to realize measurement of micro structures with nanometer accuracy.