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Model transformation based verification of Web services composition

引用

4th International Conference on Grid and Cooperative Computing - GCC 2005

作者： Yang, YanPing Tan, QingPing Xiao, Yong School of Computer Science National University of Defense Technology Changsha 410073 China National Lab. of Parallel Distributed Processing Changsha 410073 China

ISBN: (纸本)3540305106

Current Web services composition proposals, such as BPEL, BPSS, BPMN and WSCI, provide notations for describing the control and message flows in Web service collaborations. However, such proposals remain at the descriptive level, without providing any kind of mechanisms or tool support for verifying the composition specified in the proposed notations. In this paper, we present to analyze and verify Web services composition by using CP-nets. CP-nets combine the strengths of Petri nets with the expressive power of high-level programming and have sound mathematical semantics. These services composition proposals can be transformed by model transformation rules into CP-nets, which can be used to analyze the performance and to investigate behavioral properties by CP-nets specialized tools. © Springer-Verlag Berlin Heidelberg 2005.

关键词： World Wide Web

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Optimizing Yinyang K-Means Algorithm on ARMv8 Many-Core CPUs 22nd

Optimizing Yinyang K-Means Algorithm on ARMv8 Many-Core CPU...

引用

22nd International Conference on Algorithms and Architectures for parallel processing, ICA3PP 2022

作者： Zhou, Tianyang Wang, Qinglin Yin, Shangfei Hao, Ruochen Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China School of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783031226762

K-Means algorithm is one of the most common clustering algorithms widely applied in various data analysis applications. Yinyang K-Means algorithm is a popular enhanced K-Means algorithm that avoids most unnecessary calculations using triangle inequality. However, Yinyang K-Means algorithm is time-consuming when the problem size is large. Due to the influence of performance and energy-efficiency, ARM CPUs have appeared in high performance computing. Therefore, it is very interesting to accelerate Yinyang K-Means algorithm on ARM CPUs. In this paper, we propose an efficient parallel implementation of Yinyang K-Means algorithm on ARMv8 many-core CPUs by means of vectorization, NUMA affinity memory optimization and data layout optimization. The experiment on two ARMv8 many-core CPUs has shown that our implementation can achieve up to 5.6 times faster than the open-source multi-threaded one of Yinyang K-Means algorithm. To the best of our knowledge, this is the first work that studies the optimization of Yinyang K-Means algorithms on ARMv8 CPUs. © 2023, Springer Nature Switzerland AG.

关键词： K-means clustering

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CRAWL: A Trace Routing Algorithm Based on Hybrid Two-Layer Topology 33rd

CRAWL: A Trace Routing Algorithm Based on Hybrid Two-Layer T...

引用

33rd International Conference on Advanced Information Networking and Applications, AINA 2019

作者： Zheng, Li-ming Long, Wen-feng Liu, Yu-Jia Sun, Wei-dong Department of Message Communication Armed Police Officer Academy Chengdu China National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9783030150341

Data distribution is a key technology for resources convergence and sharing in distributed environment. To better meet the requirement for real time data distribution in the dynamic network, a trace routing algorithm named CRAWL based on the hybrid two-layered topology is put forward. The algorithm contains an overlay topology named CBDLO, upper of which consists of multiple distributed balanced binary trees corresponding to different properties and the lower of which is an unstructured topology. CRAWL forwards the data on the lower unstructured topology in the form of random walk, so that the data can be sent to the corresponding upper topology entry. It also includes a matching algorithm named CDM for the parallel matching data properties on the upper distributed and balanced binary tree and transmitting the matched data to the nodes that are interested in the data. The experimental results show that the algorithm can effectively support large-scale data distribution in a dynamical network, reduce distribution overhead and matching delays. © 2019, Springer Nature Switzerland AG.

关键词： Routing algorithms

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parallel transposing and communication strategies for FFT on cluster of SMP architectures with multicore processors

Parallel transposing and communication strategies for FFT on...

引用

Congress on Image and Signal processing, CISP

作者： Yuan, Jie Wu, Jian-Ping Wang, Zheng-Hua National Lab. of Parallel and Distributed Processing National University of Defense Technology Changsha China School of Computer Science National University of Defense Changsha China

ISBN: (纸本)9781424465149

This paper presents a high performance parallel formulation for 1-D FFT based on transpose algorithm. The parallel scheme of FFT trades off some efficiency for a more consistent level of parallel performance. It involves matrix transposition, and a new in-place transposing algorithm is introduced into the parallel matrix transposition to improve the efficiency. Depending on the size of the input n, the number of processes p, and the memory or network bandwidth, this method can achieve better parallel performance than the other on cluster of SMP architectures. Test shows us that our scheme can achieve a good speedup. ©2010 IEEE.

关键词： Fast Fourier transforms

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Performance analysis of end-to-end services in virtualized computing environments

Performance analysis of end-to-end services in virtualized c...

引用

11th IFIP WG 10.3 International Conference on Network and parallel Computing, NPC 2014

作者： Yan, Guofeng Peng, Yuxing School of Computer and Communication Hunan Institute of Engineering China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Science and Technology Changsha 410073 China

ISBN: (纸本)9783662449165

In this paper, we present a novel stochastic analyzing model for e2e virtualized cloud services using hierarchical Quasi-Birth Death structures (QBDs). We divide the overall virtualized cloud services into three sub-hierarchies, and then, analyze each individual sub-hierarchy using QBDs. Our approach reduces the complexity of performance analysis. Our results are useful to prevent the cloud center from entering unsafe operation, and also reveal practical insights into load balancing and capacity planning for virtualized computing environments. © 2014 IFIP International Federation for Information processing.

关键词： Stochastic systems

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A unique vertex deleting algorithm for graph isomorphism

A unique vertex deleting algorithm for graph isomorphism

引用

2011 International Symposium on Image and Data Fusion, ISIDF 2011

作者： Zhang, Baida Tang, Yuhua Wu, Junjie Huang, Linqi National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan 410073 China School of Resources and Safety Engineering Central South University Changsha 410083 China

ISBN: (纸本)9781457709692

Graph isomorphism problem has applications in many fields, such as chemistry, computer science, electronics, and network theory. But the exponential complexity of the algorithm makes the testing is time consuming. In this paper, a new algorithm named Unique Vertex Delete (UVD for short) is presented to speed up the process of isomorphic testing. The main idea of UVD algorithm is deleting vertex continuously to reduce the scale of the problem, and new field is added for each vertex to indicate the information of deleted neighbor vertices. Theoretical analysis and experiments show that the UVD algorithm consistently and significantly outperforms existing state-of-the-art approaches. © 2011 IEEE.

关键词： Set theory

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Unified weighted label propagation algorithm using connection factor 12th

Unified weighted label propagation algorithm using connectio...

引用

12th International Conference on Advanced Data Mining and Applications, ADMA 2016

作者： Wang, Xin Jian, Songlei Lu, Kai Wang, Xiaoping College of Computer National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9783319495859

With the social networks getting increasingly larger, fast community detection algorithms like the label propagation algorithm, are attracting more attention. But the label propagation algorithm deals vertices with no proper weight, which leads to the loss in the performance. We propose the connection factor of the vertex to measure its influence on the local connectivity. The connection factor can reveal the topological structure feature, and we propose a unified weight to modify the original label propagation algorithm. Experiments show that our Unified Weighted LPA has an average performance promotion from 5% to 10 %, in the best case more than 30%. © Springer International Publishing AG 2016.

关键词： Population dynamics

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A knowledge graph embedding method based on neural network 5

A knowledge graph embedding method based on neural network

引用

5th IEEE International Conference on Data Science in Cyberspace, DSC 2020

作者： Li, Chenchen Li, Aiping Tu, Hongkui Wang, Ye Wang, Changhai National University of Defense Technology College of Computer ChangSha China National University of Defense Technology College of Computer Science and Technology on Parallel and Distributed Processing Laboratory ChangSha China

ISBN: (数字)9781728195582

ISBN: (纸本)9781728195582

As the basis of many knowledge graph completion tasks, the embedding representation of entities and relations in knowledge graph (KG) is an important task in the fields of Natural Language processing (NLP) and Artificial Intelligence (AI). While most of the existing knowledge graph embedding (KGE) models based on convolutional neural network (CNN) can obtain abundant feature embedding, they may ignore an important fact that the triples in the KG come from the text, as they simply learn about the feature embedding of entities and relations without considering contextual information. Therefore, in this paper, we propose an effective KGE model based on neural network. First of all, we convert the triple (h, r, t) of the KG into a sentence [h r t]. Then, the LSTM neural network is used to learn the long-term dependence of sentences from the input feature vectors. Then, on this basis, the two-layer convolutional neural network with several different filters is used to extract different local features. Finally, the obtained feature vectors are connected together, and the inner product is carried out with the weight vectors to obtain the score of the triple, so as to judge the validity of the given triple. We evaluate our model on two benchmark datasets FB15k-237 and WN18RR, the experimental results show that the model can effectively improve the accuracy of link prediction, achieving better results compared with other baseline models. © 2020 IEEE.

关键词： Knowledge graph

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Deep learning for social network information cascade analysis: A survey 5

Deep learning for social network information cascade analysi...

引用

5th IEEE International Conference on Data Science in Cyberspace, DSC 2020

作者： Gao, Liqun Zhou, Bin Jia, Yan Tu, Hongkui Wang, Ye Chen, Chenguang Wang, Haiyang Zhuang, Hongwu National University of Defense Technology College of Computer ChangSha China National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory ChangSha China

ISBN: (纸本)9781728195582

The phenomenon of information dissemination in social networks is widespread, and Social Network Information Cascade Analysis (SNICA) aims to acquire valuable knowledge in the process of information dissemination in social networks. As the number, volume, and resolution of social network data increase rapidly, traditional social network data analysis methods, especially the analysis method of social network graph (SNG) data becoming overwhelmed in SNICA. Recently, deep learning models have changed this situation, and it has achieved success in SNICA with its powerful implicit feature extraction capabilities. In this paper, we provide a comprehensive survey of recent progress in applying deep learning techniques for SNICA. We first introduce related concepts and summarize the advantages of deep learning technology in SNICA. Then, we propose a general framework for deep learning technology, which applies to SNICA. Then, different SNICA application scenarios in the framework are classified and discussed according to user behavior analysis, information cascade analysis, rumor detection, and social network event analysis. Finally, we discuss the limitations of current work and suggest future directions. © 2020 IEEE.

关键词： Data mining

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Synchronization error detection of MPI programs by symbolic execution 21

Synchronization error detection of MPI programs by symbolic ...

引用

21st Asia-Pacific Software Engineering Conference, APSEC 2014

作者： Fu, Xianjin Chen, Zhenbang Huang, Chun Dong, Wei Wang, Ji Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781479974252

Asynchrony based overlapping of computation and communication is commonly used in MPI applications. However, this overlapping introduces synchronization errors frequently in asynchronous MPI programming. In this paper, we propose a symbolic execution based method for detecting input-related synchronization errors. The path space of an MPI program is systematically explored, and the related operations of the synchronization errors in the program are checked specifically. In addition, two optimizations are proposed to improve the efficiency. We have implemented our method as a prototype tool based on the symbolic executor Cloud9. The results of the extensive experiments indicate the effectiveness of our method. © 2014 IEEE.

关键词： Synchronization

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