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2022 6th International Conference on Mechanics, Mathematics and Applied Physics, ICMMAP 2022

作者： Liu, Pan Zhou, Yinzhao Xiong, Wenbin Liu, Chencheng Liu, Jie Liu, Gongjie Tang, Zhangchun Gao, Qiang Tianfu Innovation Energy Establishment Chengdu610000 China Nuclear and Radiation Safety Center MEE Beijing100000 China Central South University of Forestry and Technology Changsha410000 China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China Beijng PARATERA Technology Corp. Ltd Beijing100000 China University of Electronic Science and Technology of China Chengdu610000 China

Volume ignition is a method of igniting a fuel as a whole by simultaneously achieving ignition conditions throughout the fuel zone. The basic criterion for ignition is that the thermonuclear energy is greater than the energy leakage at the fuel boundary, resulting in self-sustaining heating and deep combustion. Deuterium-tritium fuels are wrapped in medium to high Z media to reduce radiative leakage and achieve lower-temperature holistic ignition and non-equilibrium combustion, ultimately allowing the fuel to achieve high combustion efficiency. Volume ignition is the use of energy balance relations under the local thermodynamic equilibrium approximation to establish the energy balance equation for thermonuclear systems, and the system ignition threshold is obtained by solving this equation. By understanding the physical process, we believe that the non-equilibrium process is universal to the volume ignition process. Changes in external factors (density, boundaries, albedo, etc.) at the moment of ignition can have a significant impact on the development direction of the system, and an ignition system with a large surface density can nevertheless withstand a large amount of reverse work and continue to burn. The design of the ignition target tries to avoid these factors through margin design, but conversely, the rational use of these laws can further improve the design margin of the capsule. With the aid of big data, the volume ignition method is easier to calculate and has a shorter iteration time. The traditional way is to propose a model, set the material, and then perform the calculation while using big data can set any model and material for calculation. In this paper, a simple comparison will be made to find out that the efficiency of the physical design of a volume ignition target will be effectively improved with the aid of big data. Volume ignition targets can be used not only in Z-pinch-driven systems but also for laser-driven volume ignition. © Published un

关键词： Ignition

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A GPU-based Fast Solution for Riesz Space Fractional Reaction-Diffusion Equation

A GPU-based Fast Solution for Riesz Space Fractional Reactio...

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International Conference on Network-Based Information Systems (NBIS)

作者： Qinglin Wang Jie Liu Chunye Gong Yang Zhang Zuocheng Xing Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China College of Aerospace Science and Engineering National University of Defense Technology Changsha China Science and Technology on Space Physics Laboratory Beijing China

The fast numerical solutions of Riesz fractional equation have computational cost of O(NMlogM), where M, N are the number of grid points and time steps. In this paper, we present a GPU-based fast solution for Riesz space fractional equation. The GPU-based fast solution, which is based on the fast method using FFT and implemented with CUDA programming model, consists of parallel FFT, vector-vector addition and vector-vector multiplication on GPU. The experimental results show that the GPU-based fast solution compares well with the exact solution. Compared to the known parallel fast solution on 8-core Intel E5-2670 CPU, the overall performance speedup on NVIDIA GTX650 GPU reaches 2.12 times and that on NVIDIA K20C GPU achieves 10.93 times.

关键词： Graphics processing units Instruction sets Mathematical model Arrays Yttrium Approximation methods parallel processing

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SCQR - A P2P Query Routing Algorithm Based on Semantic Cluster

SCQR - A P2P Query Routing Algorithm Based on Semantic Clust...

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International Symposium on Intelligent Ubiquitous Computing and Education

作者： Shiyao Jin Gui-Ming Zhu School of Computer Science National University of Defense Technology Changsha China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

The low efficiency and uncertainty routing is correct is a problem for resource location of an unstructured p2p network. It is hard to achieve high query hit with small cost and low latency for such kind of network. In this paper, we present a p2p query routing algorithm which is based on semantic cluster (SCQR). SCQR makes nodes clustered according to their semantic, and each cluster elects a super-node as cluster computing node which is responsible for computing cluster semantic and establishing links with all neighbor cluster computing nodes. Query is routed among cluster computing nodes. SCQR achieves high query hit with small routing latency and query cost in both analytical theoretical and experimental studies.

关键词： Query processing Clustering algorithms Peer to peer computing Routing Delay Costs Computer networks Frequency Floods Intelligent networks

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Benchmarking the Powering Computations for Application Tuning

Benchmarking the Powering Computations for Application Tunin...

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International Conference on Software Analysis, Testing and Evolution (SATE)

作者： Yongang Che Chuanfu Xu Zhenghua Wang Computer College National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory (PDL) National University of Defense Technology Changsha China

ISBN: (纸本)9781509045181

Powering is an important operation in many computation intensive workloads. This paper investigates the performance of different styles to calculate the powering operations from the application level. A series of small benchmark codes that calculate the powering operations in different ways are designed. Their performance is evaluated on Intel Xeon CPU under Intel compilation environments. The results show that the number of floating-point operations and the related runtime are sensitive to the value of the exponent Y and how it is used. When Y is an immediate integer number whose value is known at compile time, the cost of powering is much less than the situation when Y is an integer variable whose value is known at runtime. When Y is defined as a real variable, the cost of powering is always high, be it equals to an integer number or not. Based on the investigations, performance optimizations are applied to a kernel subroutine from a real-world supersonic combustion simulation code, which intensively involves powering operations. The result shows that the performance of that subroutine is improved for 13.25 times on the Intel Xeon E5-2692 CPU.

关键词： Benchmark testing Arrays Libraries Runtime Signal processing algorithms Hardware

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parallel Implementation of SHA256 on Multizone Heterogeneous Systems

Parallel Implementation of SHA256 on Multizone Heterogeneous...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Yongtao Luo Jie Liu Tiaojie Xiao Chunye Gong Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Digitizing program for Frontier Equipment National University of Defense Technology Changsha China National Supercomputer Center in Tianjin Tianjin China

SHA-256 plays an important role in widely used applications, such as data security, data integrity, digital signatures, and cryptocurrencies. However, most of the current optimized implementations of SHA-256 are based on CPUs or dedicated hardware, such as ASICs and FPGAs. Consequently, there is a need to explore whether new heterogeneous parallel framework can improve the computational performance of the hash function. To address this issue, we conducted a study on the MT-3000 platform, which is a special architecture processor for the next-generation exascale prototype supercomputer. We proposed MT-SHA256, a heterogeneous multistage parallel implementation for hashing multiple messages on the MT-3000. Combining the architectural features of this processor, we developed an effective solution that significantly improved the computational performance of SHA-256. As a result, MT-SHA256 achieved a maximum throughput of 1045.68 MB/s on a single acceleration core of MT-3000. This is 9.84x higher than the C code implementation on one CPU core of MT-3000. We also performed a scalability test and found that MT-SHA256 achieved a throughput of 98.04 GB/s on a computing node, and extended to 512 nodes (2048 acceleration clusters) on this system with good scalability.

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Improved algorithm for reconstructing singular connection in multi-block CFD applications

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Transactions of Nanjing University of Aeronautics and Astronautics 2013年第SUPPL.1期30卷 51-57页

作者： Wang, Yongxian Zhang, Lilun Che, Yonggang Xu, Chuanfu Liu, Wei Liu, Huayong Wang, Zhenghua College of Computer National University of Defense Technology Changsha 410073 China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China State Key Laboratory of Aerodynamics Mianyang 621000 China

An improved algorithm is proposed for the reconstruction of singular connectivity from the available pairwise connections during preprocessing phase. To evaluate the performance of the algorithm, an in-house computational fluid dynamics (CFD) code is used in which high-order finite-difference method for spatial discretization running on the Tianhe-1A supercomputer is employed. Test cases with a varied amount of mesh points are chosen, and the test results indicate that the improved singular connection reconstruction algorithm can achieve a speedup of 2000× at least when compared with the naive search method adopted in the former version of our code. Moreover, the parallel efficiency can benefit from the strategy of local communication based on the algorithm.

关键词： Finite difference method

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A mesh quality discrimination method based on convolutional neural network

A mesh quality discrimination method based on convolutional ...

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IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

作者： Zhenpeng Xu Xinhai Chen Lihua Chi Jie Liu Chunye Gong Science and Technology on Parallel and Distributed Processing Laboratory & Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (数字)9781728170053

ISBN: (纸本)9781728170060

With the rapid development of highperformance computing, computational fluid dynamics (CFD) has become an important part of hydrodynamics and aerodynamics. Mesh quality is the key factor that affects the accuracy and efficiency of CFD numerical calculation. However, the current the process of mesh quality discrimination is very time-consuming. The manpower time needed for this process takes up a large proportion in the whole numerical calculation process. A large number of artificial intelligence algorithms have been put forward to replace the human to efficiently complete all kinds of tedious tasks. In this paper, we propose a convolutional neural network (CNN) based mesh quality discrimination method, MeshNet. MeshNet uses residual neural network structure to learn mesh features and automatically judge the mesh quality. The experimental results show that the proposed network can greatly save labor time cost and achieve an accuracy of 94.41% for mesh quality discrimination.

关键词： Convolution Computational fluid dynamics Convolutional neural networks Jacobian matrices Artificial intelligence distributed processing Software engineering

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A Novel Deep Neural Network Model for Credit Risk Prediction of Chinese Farmers

A Novel Deep Neural Network Model for Credit Risk Prediction...

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IEEE International Conference on Data science in Cyberspace (DSC)

作者： Yalong Xie Aiping Li Ziniu Liu Kai Chen Hongkui Tu College of Computer National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781665418164

China is a big agricultural county with more than 500 million rural population. In China, farmers usually loan from rural commercial banks or rural credit cooperatives. It is crucial for the national economic development and the improvement of people's standard of living that how to reasonably use funds to subsidize the agricultural population and reduce the risk of rural loans. At present, credit risk prediction of farmers mainly depends on the experience of experts in the business field, and there is little published research on using artificial intelligence methods to solve this problem. This paper presents a complete set of methods, including data collection, feature selection, etc. We propose a novel deep neural network model named DNN-CRP for credit risk prediction of Chinese framers. Experiments on an actual credit loan dataset of Chinese farmers are presented, and experimental results show that the comprehensive performance of the DNN-CRP model is better than current state-of-the-art models. It is believed that the DNN-CRP model proposed in this paper can help banks improve the efficiency of the credit loan business of farmers and reduce credit risks.

关键词： Deep learning Sensitivity Neural networks Sociology Predictive models Data collection Data models

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Large-scale Network Topology Generation for Emulation Environment

Large-scale Network Topology Generation for Emulation Enviro...

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The First International Conference on Networking and distributed Computing(第一届网络与分布式计算国际会议 ICNDC 2010)

作者： Xu Fei Li Jin Kuang Xiao-hui Huang Min-huan Che Yong-gang National Key Laboratory of Science and Technology on Information System Security Beijing Institute National Key Laboratory of Science and Technology on Information System Security Beijing Institute National Laboratory for Parallel and Distributed Process National University of Defense Technology

Network emulation environment is great importance to the research of network protocols, applications and security mechanism. Large-scale network topology generation b one of key technologies to construct network emulation environment. In this paper, a new large-scale network topology generation framework called LSNTGF is proposed, which divides the network topology into three hierarchies: AS, router and terminal node. It contains the assignment mechanism to bandwidth of each link and IP address of each node. The framework is evaluate by implementation, and the result illustrate it is efficient to network emulation environment for network protocols and security research.

关键词： Large-scale network topology generation bandwidth assignment IP address assignment

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Simulation of Nuclear Reactor Accident Scenarios using Physics-Informed Neural Networks and Transfer-Learning 4

Simulation of Nuclear Reactor Accident Scenarios using Physi...

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4th International Conference on Electronic Information Engineering and Computer science, EIECS 2024

作者： Yu, Yang Xie, Yufei Wang, Wenlin Wu, Guohua Lan, Haitao Lin, Enbo An, Ping Sun, Zibin Zhang, Haichuan Wu, Yixian National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China Nuclear Power Institute of China Science and Technology on Reactor System Design Technology Laboratory Chengdu China School of Automation Wuhan University of Technology Wuhan China Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China Institute of Automotive Engineers Hubei University of Automotive Technology Shiyan China Nuclear Power Institute of China Chengdu China

ISBN: (纸本)9798331531409

In a Loss of Coolant Accident (LOCA), reactor core temperatures can rise rapidly, leading to potential fuel damage and radioactive material release. This research presents a groundbreaking method that combines the power of Monte Carlo Sampling and Physics-Informed Neural Networks (PINNs) to simulate and effectively address the challenging Loss of Coolant Accidents (LOCA) in nuclear reactors. In the event of a LOCA, reactor core temperatures can soar rapidly, posing a significant threat to fuel integrity and potentially leading to the release of radioactive materials. By leveraging the strengths of both Monte Carlo Sampling and PINNs, this approach aims to provide a comprehensive and accurate simulation framework for assessing and mitigating the consequences of such accidents. The method yields high prediction accuracy (MAE: 0.033, RMSE: 0.098, R2: 0.814) and demonstrates robustness through transfer learning, maintaining strong performance (MAE: 0.064, RMSE: 0.163, R2: 0.735). © 2024 IEEE.

关键词： Coolants

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