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2nd Annual International Conference on Information System and Artificial Intelligence, ISAI 2017

作者： Zhang, Wenzhe Science and Technology on Parallel and Distributed Laboratory State Key Laboratory of High Performance Computing State Key Laboratory of High-end Server and Storage Technology College of Computer National University of Defense Technology Changsha China

Dangling pointer error is pervasive in C/C++ programs and it is very hard to detect. This paper introduces an efficient detector to detect dangling pointer error in C/C++ programs. By selectively leave some memory accesses unmonitored, our method could reduce the memory monitoring overhead and thus achieves better performance over previous methods. Experiments show that our method could achieve an average speed up of 9% over previous compiler instrumentation based method and more than 50% over previous page protection based method. © Published under licence by IOP Publishing Ltd.

关键词： Errors

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CLASSIFICATION OF LAND COVER BASED ON DEEP BELIEF NETWORKS USING POLARIMETRIC RADARSAT-2 DATA

CLASSIFICATION OF LAND COVER BASED ON DEEP BELIEF NETWORKS U...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Qi Lv Yong Dou Xin Niu Jiaqing Xu Baoliang Li National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology

ISBN: (纸本)9781479953141

Urban land use and land cover (LULC) classification is one of the core applications in Geographic Information System (GIS). In this paper, a novel classification approach based on Deep Belief Network (DBN) for detailed urban mapping is proposed. Deep Belief Network (DBN) is a widely investigated and deployed deep learning model. By applying the DBN model, effective spatio-temporal mapping features can be automatically extracted to improve the classification performance. Six-date RADARSAT-2 Polarimetric SAR (PolSAR) data over the Great Toronto Area were used for evaluation. Experimental results showed that the proposed method can outperform SVM and contextual approaches using adaptive MRF.

关键词： Land cover classification Deep learning Restricted Boltzmann Machines (RBMs) Deep Belief Network (DBN) PolSAR

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KC-GenRe: A Knowledge-constrained Generative Re-ranking Method Based on Large Language Models for Knowledge Graph Completion 30

KC-GenRe: A Knowledge-constrained Generative Re-ranking Meth...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wang, Yilin Hu, Minghao Huang, Zhen Li, Dongsheng Yang, Dong Lu, Xicheng Defense Innovation Institute Academy of Military Sciences China Information Research Center of Military Science China National Key Laboratory of Parallel and Distributed Computing China

ISBN: (纸本)9782493814104

The goal of knowledge graph completion (KGC) is to predict missing facts among entities. Previous methods for KGC re-ranking are mostly built on non-generative language models to obtain the probability of each candidate. Recently, generative large language models (LLMs) have shown outstanding performance on several tasks such as information extraction and dialog systems. Leveraging them for KGC re-ranking is beneficial for leveraging the extensive pre-trained knowledge and powerful generative capabilities. However, it may encounter new problems when accomplishing the task, namely mismatch, misordering and omission. To this end, we introduce KC-GenRe, a knowledge-constrained generative re-ranking method based on LLMs for KGC. To overcome the mismatch issue, we formulate the KGC re-ranking task as a candidate identifier sorting generation problem implemented by generative LLMs. To tackle the misordering issue, we develop a knowledge-guided interactive training method that enhances the identification and ranking of candidates. To address the omission issue, we design a knowledge-augmented constrained inference method that enables contextual prompting and controlled generation, so as to obtain valid rankings. Experimental results show that KG-GenRe achieves state-of-the-art performance on four datasets, with gains of up to 6.7% and 7.7% in the MRR and Hits@1 metric compared to previous methods, and 9.0% and 11.1% compared to that without re-ranking. Extensive analysis demonstrates the effectiveness of components in KG-GenRe. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Knowledge graph

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LoGPX: A new communication model for message-passing programs

LoGPX: A new communication model for message-passing program...

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International Symposium on Performance Evaluation of Computer & Telecommunication Systems SPECTS

作者： Yufei Lin Yuhua Tang Xiaowei Guo Xinhai Xu National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

Message Passing Interface (MPI) is a de facto standard for writing high-performance message-passing applications on distributed memory systems. To design effective applications and predict the performance of future systems, an accurate communication model is needed. In this paper, we discuss the characteristics of current systems and MPI implementations, then propose a more complete communication model, named LoGPX, which synthetically captures the influences of MPI communication protocol, the invoking time of communication primitive, hardware resource and network contention. Based on the model, we obtain the condition that the message transmission cost reaches the infimum, and we show that if ignoring some factors of LoGPX model, it can be degenerated to several popular models such as LogP, LogGP, LoGPC and LogGPO.

关键词： Protocols Receivers Message passing Network interfaces Hardware Analytical models Routing

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A Trusted Remote Attestation Model Based on Trusted Computing

A Trusted Remote Attestation Model Based on Trusted Computin...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Yue Yu Huaimin Wang Bo Liu Gang Yin National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781479914449

Traditional security protocols can not be trusted in some application scenarios of high security level because the endpoints integrity is ignored. In this paper, we propose a novel trusted remote attestation model which combines the secure channel and the integrity measurement architecture of trusted computing. We design and implement a prototype system based on a mature security protocol, Transport Layer Security (TLS) protocol, integrated with integrity report provided by trusted platform module (TPM). The TLS protocol guarantees the security of data exchange process and the integrity report of TPM provides the evidence about the trustworthiness and the security state of the communication endpoints. Compared by traditional approaches, our method is more efficient and can be deployed in large scale systems easily.

关键词： Protocols Servers Principal component analysis Authentication Computer architecture Privacy

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Combining model and iterative compilation for program performance optimization

Journal of Software

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Journal of Software 2009年第3期4卷 240-246页

作者： Lu, Pingjing Che, Yonggang Wang, Zhenghua National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China

The performance gap for high performance applications has been widening over time. High level program transformations are critical to improve applications' performance, many of which concern the determination of optimal values for transformation parameters, such as loop unrolling and blocking. Static approaches achieve these values based on analytical models that are hard to achieve because of increasing architecture complexity and code structures. Recent iterative compilation approaches achieve it by executing different versions of the program on actual platforms and select the one that renders best performance, outperforming static compilation approaches significantly. But the expensive compilation cost has limited their application scope to embedded applications and a small group of math kernels. This paper proposes a combinative approach--Combining Model and Iterative Compilation for Program Performance Optimization (CMIC). Such an approach first constructs a program optimization transformation model based on hardware performance counters to decide how and when to apply transformations, and then selects the optimal transformation parameters using Nelder-Mead simplex algorithm. Experimental results show that our approach can effectively improve programs' floating-point performance, reducing programs' runtime, therefore, lessening the performance gap for high-performance applications. © 2009 ACADEMY PUBLISHER.

关键词： Digital arithmetic

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UML based statistical testing acceleration of distributed safety-critical software 04

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Proceedings of the Second international conference on parallel and distributed processing and Applications

作者： Jiong Yan Ji Wang Huo-wang Chen National Laboratory for Parallel and Distributed Processing Changsha P.R. China

ISBN: (纸本)9783540241287

It is necessary to assess the reliability of distributed safety-critical systems to a high degree of confidence before they are deployed in the field. However, distributed safety-critical software systems often include some rarely executed critical functions that are often inadequately tested in statistical testing based reliability estimation. This paper presents a method that can accelerate statistical testing of distributed safety-critical software. The method starts with the derivation of scenario usage diagram model (SUD) from UML diagrams annotated with usage related attributes and reliability attributes. Then the statistical testing accelerating method based on importance sampling is presented. When both the critical scenarios and the entire software are adequately tested, the method can still compute the unbiased software reliability from the test results with much less test cases. Thus, the statistical testing cost of distributed safety-critical software can be reduced effectively.

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VISUAL CONFUSION LABEL TREE FOR IMAGE CLASSIFICATION

VISUAL CONFUSION LABEL TREE FOR IMAGE CLASSIFICATION

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IEEE International Conference on Multimedia and Expo

作者： Yuntao Liu Yong Dou Ruochun Jin Rongchun Li National University of Defense Technology National Laboratory for Parallel and Distributed Processing Changsha China

Convolution neural network models are widely used in image classification tasks. However, the running time of such models is so long that it is not the conforming to the strict real-time requirement of mobile devices. In order to optimize models and meet the requirement mentioned above, we propose a method that replaces the fully-connected layers of convolution neural network models with a tree classifier. Specifically, we construct a Visual Confusion Label Tree based on the output of the convolution neural network models, and use a multi-kernel SVM plus classifier with hierarchical constraints to train the tree classifier. Focusing on those confusion subsets instead of the entire set of categories makes the tree classifier more discriminative and the replacement of the fully-connected layers reduces the original running time. Experiments show that our tree classifier obtains a significant improvement over the state-of-the-art tree classifier by 4.3% and 2.4% in terms of top-1 accuracy on CIFAR-100 and ImageNet datasets respectively. Additionally, our method achieves 124× and 115× speedup ratio compared with fully-connected layers on AlexNet and VGG16 without accuracy decline.

关键词： Image classification Convolution neural network Confusion graph Label tree

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Enhanced streamline texture synthesis for vector field visualization

Enhanced streamline texture synthesis for vector field visua...

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International Conference on High Performance Computing in the Asia-Pacific Region

作者： Wen Zhang Xiaomei Li National Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)0769505892

The Streamline Texture Synthesis (STS) method uses a different 1D texture to texture map each streamline and streamline textures are synthesized. The Enhanced STS (ESTS) adjusts the width of a streamline based on the critical point and maps several 1D textures to a streamline in order to accelerate computing. ESTS can also simulate animations and visualize 2D unsteady or 3D surface flows. The analyzed result proves that ESTS produces substantially better visual results and ESTS is fast enough to visualize vector field interactively.

关键词： Visualization Streaming media Pixel Sociotechnical systems Animation Convolution Image sampling Acceleration Computational modeling Filters

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Software Effective Evaluating Technology: SWEET

Software Effective Evaluating Technology: SWEET

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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Yaozong Li Tao Wang Yue Yu Dongyang Hu National Laboratory for Parallel and Distributed Processing National University of Defence Technology Changsha China

ISBN: (数字)9781728109459

ISBN: (纸本)9781728109466

In open source community, there are a large number of software resources existing. Such software resources distribute in different societies or storehouses, which require different software characteristic. This phenomenon results in difficult to evaluate software quality using traditional methods. In this case, a novel open-source software sorting algorithm may be an effective solution. Considering both subjective and objective levels, we propose a new method on software sorting and retrieving. In the subjective level, metrics are selected from the corresponding collaborative development community based on software topic. In the objective level, metrics are obtained from the group emotional evaluation value of the knowledge sharing community. We have proved the effectiveness of the method through comparison experiments. Combining with the Solrcloud tool, this method has been integrated into the OSSEAN platform.

关键词： Open source software Sorting Collaboration Software algorithms Measurement Tools

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