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arXiv 2018年

作者： Qiao, Peng Dou, Yong Chen, Yunjin Feng, Wensen Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha China ULSee Inc. Hangzhou China College of Computer Science & Software Engineering Shenzhen University Shenzhen China

Image restoration problems are typical ill-posed problems where the regularization term plays an important role. The regularization term learned via generative approaches is easy to transfer to various image restoration, but offers inferior restoration quality compared with that learned via discriminative approaches. On the contrary, the regularization term learned via discriminative approaches are usually trained for a specific image restoration problem, and fail in the problem for which it is not trained. To address this issue, we propose a generic diffusion process (genericDP) to handle multiple Gaussian denoising problems based on the Trainable Non-linear Reaction Diffusion (TNRD) models. Instead of one model, which consists of a diffusion and a reaction term, for one Gaussian denoising problem in TNRD, we enforce multiple TNRD models to share one diffusion term. The trained genericDP model can provide both promising denoising performance and high training efficiency compared with the original TNRD models. We also transfer the trained diffusion term to non-blind deconvolution which is unseen in the training phase. Experiment results show that the trained diffusion term for multiple Gaussian denoising can be transferred to image non-blind deconvolution as an image prior and provide competitive performance. Copyright © 2018, The Authors. All rights reserved.

关键词： Diffusion

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HDSVM: A High Efficiency distributed SVM Framework over Data Stream

HDSVM: A High Efficiency Distributed SVM Framework over Data...

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IEEE International Symposium on parallel and distributed processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Yan Hou Yijie Wang Xingkong Ma Li Cheng College of Computer National University of Defense Technology Changsha National Laboratory for Parallel and Distributed Processing China

ISBN: (纸本)9781538637913

The application of Support Vector Machine (SVM) over data stream is growing with the increasing real-time processing requirements in classification field, like anomaly detection and real-time image processing. However, the dynamic live data with high volume and fast arrival rate in data streams make it challenging to apply SVM in data stream processing. Existing SVM implementations are mostly designed for batch processing and hardly satisfy the efficiency requirement of stream processing for its inherent complexity. To address the challenges, we propose a high efficiency distributed SVM framework over data stream (HDSVM), which consists of two main algorithms, incremental learning algorithm and distributed algorithm. Firstly, we propose a partial support vectors reserving incremental learning algorithm (PSVIL). By selecting a subset of support vectors based on their distances to classification hyperplane instead of the universal set to update SVM, the algorithm achieves lower time overhead while ensuring accuracy. Secondly, we propose a distribution remaining partition and fast aggregation distributed algorithm (DRPFA) for SVM. The real-time data is partitioned based on the original distribution with clustering instead of random partition, and historical support vectors are partitioned based on their distances to the classification hyperplane. The global hyperplane can be obtained by averaging the parameters of local hyperplanes due to the above partition strategy. Extensive experiments on Apache Storm show that the proposed HDSVM achieve lower time overhead and similar accuracy compared with the state-of-art. Speed-up ratio is increased by 2-8 times within 1% accuracy deviation.

关键词： Support vector machines Training distributed databases distributed algorithms Real-time systems Partitioning algorithms Streaming media

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A Review of Indoor-Outdoor Scene Classification

A Review of Indoor-Outdoor Scene Classification

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2017 2nd International Conference on Control, Automation and Artificial Intelligence(CAAI2017)

作者： Zhehang Tong Dianxi Shi Bingzheng Yan Jing Wei National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology

ISBN: (纸本)9781510845541

Indoor-Outdoor scene classification problem have been proposed for almost 20 years and widely applied to general scene classification, image retrieval, image processing and robot application. But there is no consensus on one particular scene classification technique that can solve the Indoor-Outdoor scene classification problem perfectly. As larger image dataset has been developed and machine learning technology especially deep learning based methods achieve remarkable performance in computer vision, we aim to provide guidance and direction for researchers to tackle the Indoor-Outdoor scene classification problem with more powerful and robust solution through concluding the Indoor-Outdoor scene classification approaches which have been proposed in last 20 years. In this paper, we review the Indoor-Outdoor scene classification including feature extraction, classifier and related dataset. Their advantages and disadvantages are discussed. At last we conclude some challenging problems remain unsolved and propose some potential solutions.

关键词： indoor-outdoor scene classification computer vision

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Mechanism of floating body effect mitigation via cutting off source injection in a fully-depleted silicon-on-insulator technology

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Chinese Physics B 2016年第3期25卷 283-289页

作者：黄鹏程陈书明陈建军 College of Computer National University of Defense Technology Changsha 410073 China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

In this paper, the effect of floating body effect （FBE） on a single event transient generation mechanism in fully depleted （FD） silicon-on-insulator （SOI） technology is investigated using three-dimensional technology computer-aided design （3D- TCAD） numerical simulation. The results indicate that the main SET generation mechanism is not carder drift/diffusion but floating body effect （FBE） whether for positive or negative channel metal oxide semiconductor （PMOS or NMOS）. Two stacking layout designs mitigating FBE are investigated as well, and the results indicate that the in-line stacking （IS） layout can mitigate FBE completely and is area penalty saving compared with the conventional stacking layout.

关键词： floating body effect in-line stacking silicon-on-insulator source injection

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Effect of supply voltage and body-biasing on single-event transient pulse quenching in bulk fin field-effect-transistor process

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Chinese Physics B 2016年第4期25卷 495-500页

作者：于俊庭陈书明陈建军黄鹏程宋睿强 College of Computer National University of Defense Technology Changsha 410073 China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

Charge sharing is becoming an important topic as the feature size scales down in fin field-effect-transistor （FinFET） technology. However, the studies of charge sharing induced single-event transient （SET） pulse quenching with bulk FinFET are reported seldomly. Using three-dimensional technology computer aided design （3DTCAD） mixed-mode simulations, the effects of supply voltage and body-biasing on SET pulse quenching are investigated for the first time in bulk FinFET process. Research results indicate that due to an enhanced charge sharing effect, the propagating SET pulse width decreases with reducing supply voltage. Moreover, compared with reverse body-biasing （RBB）, the circuit with forward body-biasing （FBB） is vulnerable to charge sharing and can effectively mitigate the propagating SET pulse width up to 53% at least. This can provide guidance for radiation-hardened bulk FinFET technology especially in low power and high performance applications.

关键词： body-biasing SET pulse quenching charge sharing bulk FinFET process

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A Scalable and Flexible Monitoring System Framework for Supercomputers

A Scalable and Flexible Monitoring System Framework for Supe...

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2017 International Conference on computer, Electronics and Communication Engineering(CECE2017)

作者： Tong XIAO Kai LU College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

Mankind's demand for more powerful computing capabilities is never met, which has led to the continuous improvement of supercomputers' performance. A more powerful supercomputer tends to have a larger system scale, which brings serious challenges to the system management, within which how to monitor the system's state is a critical problem. To address this problem, a scalable and flexible monitoring system framework for supercomputers is brought forward in this paper which can monitor supercomputers with tens of thousands of nodes effectively and efficiently. In this paper, we firstly give an overview of the framework and then focus on the Super computer System Description Language(SCSDL) which is key to the framework. In the end, we explain some techniques about implementing the framework, and the client GUIs of a job monitoring system and an error monitoring system for Tianhe-2 based on this framework are given, from which we can see that the framework is well scalable and flexible to monitor Tianhe-2 which has 16,000 nodes effectively and efficiently.

关键词： Monitoring system Framework Supercomputer Scalable Flexible

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Efficient detection of dangling pointer error for C/C++ programs 2

Efficient detection of dangling pointer error for C/C++ prog...

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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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Automatic generation of fast BLAS3-GEMM: A portable compiler approach 17

Automatic generation of fast BLAS3-GEMM: A portable compiler...

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International Symposium on Code Generation and Optimization (CGO)

作者： Xing Su Xiangke Liao Jingling Xue College of Computer National Laboratory for Parallel and Distributed Processing Changsha China UNSW School of Computer Science and Engineering Sydney NSW Australia

ISBN: (纸本)9781509049318

GEMM is the main computational kernel in BLAS3. Its micro-kernel is either hand-crafted in assembly code or generated from C code by general-purpose compilers (guided by architecture-specific directives or auto-tuning). Therefore, either performance or portability suffers. We present a POrtable Compiler Approach, Poca, implemented in LLVM, to automatically generate and optimize this micro-kernel in an architecture-independent manner, without involving domain experts. The key insight is to leverage a wide range of architecture-specific abstractions already available in LLVM, by first generating a vectorized micro-kernel in the architecture-independent LLVM IR and then improving its performance by applying a series of domain-specific yet architecture-independent optimizations. The optimized micro-kernel drops easily in existing GEMM frameworks such as BLIS and OpenBLAS. Validation focuses on optimizing GEMM in double precision on two architectures. On Intel Sandybridge and AArch64 Cortex-A57, Poca's micro-kernels outperform expert-crafted assembly code by 2.35% and 7.54%, respectively, and both BLIS and OpenBLAS achieve competitive or better performance once their micro-kernels are replaced by Poca's.

关键词： Kernel Optimization computer architecture Linear algebra Libraries Programming Program processors

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Image Annotation by Object Hypotheses-oriented Deep Neural Networks

Image Annotation by Object Hypotheses-oriented Deep Neural N...

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2017 2nd International Conference on Software, Multimedia and Communication Engineering（SMCE 2017)

作者： Fang MA Shao-he LV Ke-xin ZHENG Chi JIN Fei CHEN Ke YANG and Yong DOU National Laboratory for Parallel and Distributed Processing National University of Defense Technology University of South China School of Computer Science and Technology

Image annotation generates a set of semantic labels that describe the contents of an input *** deep learning techniques have achieved significant success in many areas of image *** this paper,we present a multi-label image annotation method that combines unsupervised object hypotheses generation and deep neural *** an image,object hypotheses are generated in an unsupervised *** we extract the image features for each hypothesis with a deep neural network *** combining the features of all hypotheses,we get the features of the entire ***,we calculate for each label the probability of that the label is correlated with the given *** can be trained in an end-to-end way using the standard backward propagation *** results on multiple benchmark datasets show that our method is better than the state-of-the-art ones.

关键词： Deep learning Multi-label annotation Object hypotheses

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A novel open source software ecosystem: From a graphic point of view and its application 28

A novel open source software ecosystem: From a graphic point...

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28th International Conference on Software Engineering and Knowledge Engineering, SEKE 2016

作者： Song, Chenxi Wang, Tao Yin, Gang Zhang, Xunhui Yang, Cheng National Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)189170639X

With the rapid development of open source software, various elements such as OSS, developers, users and online posts, across different communities and their interactions constitute a novel software ecosystem. Most of the current researches about software ecosystems care the connections between software, and few of them consider the relationship across communities from an overall perspective, and fail to cover the users and their activities which should be an indispensable part of the OSS ecosystem. This paper model the OSS ecosystem as a graph, which combines different types of OSS communities as a whole. Based on this graph model, we analyze the characteristics of ecosystem, like the evolution, competition and symbiosis. In addition, we build a recommendation system as well, and the experiment results suggest the validation of our approach. Copyright © 2016 by KSI Research Inc. and Knowledge Systems Institute Graduate School.

关键词： Ecosystems

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