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, 11.3x. The experimental result proves that the GPU platform combined with the MATLAB language is a good combination for complex network research.
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.
Spike neural networks are inspired by animal brains,and outperform traditional neural networks on complicated tasks.However,spike neural networks are usually used on a large scale,and they cannot be computed on commercial,off-the-shelf computers.A parallel architecture is proposed and developed for discrete-event simulations of spike neural networks.Furthermore,mechanisms for both parallelism degree estimation and dynamic load balance are emphasized with theoretical and computational analysis.Simulation results show the effectiveness of the proposed parallelized spike neural network system and its corresponding support components.
Here, we used the micro P-scan method to investigate the saturated absorption(SA) of different layered Bi_2Se_3 continuous films. Through resonance excitation, first, we studied the influence of the second surface state(SS) on SA. The second SS resonance excitation(～2.07 e V) resulted in a free carrier cross section that was 4 orders of magnitude larger than usual. At the same time, we found that the fast relaxation process of the massless Dirac electrons is much shorter than that of electrons in bulk states. Moreover, the second SS excitation resonance reduced the saturation intensity. Second, we studied the effect of the thickness on the SA properties of materials.The results showed that the saturation intensity was positively correlated to the thickness, the same as the modulation depth, and the thicker the Bi_2Se_3 film was, the less the second SS would influence it. This work demonstrated that by using Bi_2Se_3 as a saturable absorber through changing the thickness or excitation wavelength, a controllable SA could be achieved.
JUN ZHANGTIAN JIANGTONG ZHOUHAO OUYANGCHENXI ZHANGZHENG XINZHENYU WANGXIANG’AI CHENG
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.
