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In this paper, fuzzy set theory is applied to a quantitative way of assigning importance class to coronal mass ejection (CME) events based on four observed characteristics, i.e. velocity, span, mass and kinetic energy. The weights to be associated with each of the characteristics and the membership functions of belonging to one of the three importance classes are determined from the correlations between the characteristics and the CME morphology properties. A useful software of data reduction has been successfully compiled. The results show that the fuzzy comprehensive evaluation is better than the classic statistical analysis.

Prompted by the observational result that in He-3-rich events the energetic He-3 and heavy ions exhibit similar power-law distributions, we study by means of numerical solution of Fokker-Planck equation, the characteristics of the evolution of the distribution of ions after they are accelerated by Alfven turbulence. The results of computation show that the plasma density in the source region of acceleration and the energy density of Alfven turbulence play the chief role in the energy spectrum of the particles. For a plasma density n = (0.1 - 1) 10(10) cm(-3) a magnetic field B = 50 - 100 G and a turbulence energy density 0.4-2 ergs cm(-3) the turbulent Alfven waves can accelerate He-3 and heavy ions to the order of magnitude of 10 MeV/nucleon then in about 1 second. The index of the energy spectrum is 2.0-3-5. The result of the theoretical calculation basically agrees with the observation.

With the development of the electronic technology, the processors count in a supercomputer reaches million scale, making the fault problem becomes a fundamental issue for massive parallel CFD simulation. Checkpoint/Rollback technology is a widely used fault tolerant method, and has a obvious affect for massive parallel application. In this paper, we explore the checkpoint method for the CFD simulation with the CFD simulation features, and analysis the two checkpoint strategies: fine granularity checkpoint and coarse checkpoint. We analysis the checkpoint intervals and the volume of the backup data, and their impact on the FT overhead through model. Experimental results on the Tianhe-2 supercomputer demonstrate that coarse checkpoint can achieve a much better FT effect for the CFD simulation.

When a filament in an active region quickly ascends, the underlying current sheets reconnect with one another and produce strong electric fields, which may accelerate electrons. On the basis of this physical process and by means of solving the Fokker-Planck equation, which includes Coulomb collisions and ion-acoustic turbulent scattering, the evolutionary characteristics of electron distribution function have been obtained. The results of calculations show that (1) When the intensity of electric field is 1–10V cm −1 , then in 10 −5 –10 −6 s electrons may be accelerated to the order of 0.1–1 MeV; (2) The accelerated electrons approximately exhibit power-law distribution and its spectral index basically coincides with that inferred from the microwaves and hard X-rays of flares during the impulsive phase.

High Performance Computing (HPC) is increasingly being used in Computational Fluid Dynamics (CFD) simulation for acceleration. However, CFD simulation faces serious reliability problems, and fault tolerant technology must be taken to ensure the efficient execution of the large-scale parallel CFD simulation. In this paper, we propose an application-level synchronous checkpoint-recover method for parallel CFD simulation on the basis of the application features of CFD simulation. In this method, the periodic snapshot output in the CFD simulation is naturally treated as a blocking coordinated checkpoint, and all the processes can resume the execution from the latest checkpoint with an arbitrary number of fail processes. We design the synchronous checkpoint-recovery framework for CFD simulation, and implement it in the open source software Open FOAM. Experimental results demonstrate that our method can well support the fault tolerant in large-scale parallel CFD applications with very little additional overhead on the original cost of CFD periodic snapshot output.

Magnetic change memory, resistive change memory, phase change memory are promising non-volatile memory whose file system is worthy of study. Because the memristor is not commercial yet, few works focus on the file system of memristor. This paper presents a scheme of file system as well as data management based on memristor. What's more, the data comparison in the file system oriented to memristor is designed based on its state logic function. It can reduce the number of reading and writing data in file system and the CPU computing time.

In this paper, the observational data of H α , radio, soft X-ray, hard X-ray and γ-ray for the 3B/X3.0 solar flare on February 4, 1986 are collected. This flare is studied comprehensively by using the current loop coalescence model. The results show that the solar flare on Feb. 4, 1986 results from the coalescence instability between the filament current loops, and a sequence of H α photographs taken at the Urumqi Astronomical Station provide an observational evidence of filament current loops coalescence. The high energy data for Feb.4, 1986 flare further corrobrate that the coalescence instability is an efficient mechanism for the simultaneous acceleration of high energe particles during the flare.

With fast development of GPU hardware and software, using GPUs to accelerate non-graphics CPU applications is becoming inevitable trend. GPUs are good at performing ALU-intensive computation and feature high peak performance; however, how to harness GPUs' powerful computing capacity to accelerate the applications in the field of scientific computing still remains a big challenge. In this paper, we implement the whole application Mgrid taken from Spec2000 benchmarks on an AMD GPU and propose several optimization strategies for stencil computations in the naive GPU code. We first improve thread utilization through using vector types and multiple output streams mechanism provided by the Brook+ programming language. By tuning thread granularity, we try to hit the right balance between locality within each thread and parallelism among threads. Then, we reorganize the stream layout by transforming the 3D data stream into the 2D stream in the block manner. Through stream reorganization, more data locality in the cache is exploited. Further, we propose branch elimination to convert control dependence to data dependence, catering to GPUs' powerful ALU-intensive processing capability. Finally, we redistribute computations between CPU and GPU to make more advisable computing resources usage considering different problem sizes. We demonstrate the effectiveness of our proposed optimization strategies on an AMD Radeon HD4870 GPU using the Brook+ programming language. Using a double-precision floating-point implementation, the experimental results show that the optimized GPU version of Mgrid gains 2.38x speedup compared to the naive GPU code and obtains as high as 15.06x speedup versus the CPU implementation run on an Intel Xeon E5405 CPU.

The time management (TM) is concerned with ensuring that the execution of the parallel discrete event simulation is properly synchronized. This is particularly important for simulations, not only to ensure that events are processed in a correct order, but also to ensure that repeated executions of a simulation with the same inputs produce exactly the same results. The goal of the synchronization mechanism was to ensure that each LP processes events in time-stamp order. This requirement was referred to as the local causality constraint (LCC). This paper begins with introduction of synchronization mechanisms, and then comparatively discusses conservative algorithms and optimistic algorithms. Finally we emphatically provide and describe the implementation of a new optimized algorithm, termed as the flexible cycle algorithm, which solve the fatal problems of conservative or optimistic algorithms, resulting in the best of both methods.

AR 5395 was the super-active region in Solar cycle 22. In this active region, there was rapid relative motion of magnetic elements, growth and decay of umbrae, frequent newly emerging magnetic flux and various mass motions.Data include daily vector magnetograms (Huairou Observing Station, Beijing Observatory, Hα filtergrams and photographs of sunspot group with fine structures (Yunnan Obs. and Purple Mountain Obs.) on March 9 - 15, 1989. In this period 42 flares have been observed by Yunnan and Purple Mountain Obs. (table 1). Observational data showed that all the 42 flares occurred in four segments (marked as A,B,C,D) of U-shaped neutral line in this active region (Fig. 1).

The two-ribbon flare of May 13, 1981 is one of the most notable flares during solar cycle 21. There are rich observational data of this flare. We study carefully the characteristics about the evolution and motion of the filament related with the flare as well as the relationship between these characteristics and the development of the flare. The results indicate that the increase of the filament current plays an important role in the occurrence and development of the flare.

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.

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.

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.