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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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HPDedup: A hybrid prioritized data deduplication mechanism for primary storage in the cloud

arXiv

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arXiv 2017年

作者： Wu, Huijun Wang, Chen Fu, Yinjin Sakr, Sherif Zhu, Liming Lu, Kai Data61 CSIRO University of New South Wales Australia PLA University of Science and Technology China Science and Technology on Parallel and Distributed Laboratory State Key Laboratory of High Performance Computing State Key Laboratory of High-end Server & Storage Technology College of Computer National University of Defense Technology Changsha China

—Eliminating duplicate data in primary storage of clouds increases the cost-efficiency of cloud service providers as well as reduces the cost of users for using cloud services. Most existing primary deduplication techniques either use inline caching to exploit locality in primary workloads or use post-processing deduplication running in system idle time to avoid the negative impact on I/O performance. However, neither of them works well in the cloud servers running multiple services or applications for the following two reasons: Firstly, the temporal locality of duplicate data writes may not exist in some primary storage workloads thus inline caching often fails to achieve good deduplication ratio. Secondly, the post-processing deduplication allows duplicate data to be written into disks, therefore does not provide the benefit of I/O deduplication and requires high peak storage capacity. This paper presents HPDedup, a Hybrid Prioritized data Deduplication mechanism to deal with the storage system shared by applications running in co-located virtual machines or containers by fusing an inline and a post-processing process for exact deduplication. In the inline deduplication phase, HPDedup gives a fingerprint caching mechanism that estimates the temporal locality of duplicates in data streams from different VMs or applications and prioritizes the cache allocation for these streams based on the estimation. HPDedup also allows different deduplication threshold for streams based on their spatial locality to reduce the disk fragmentation. The post-processing phase removes duplicates whose fingerprints are not able to be cached due to weak temporal locality from disks. The hybrid deduplication mechanism significantly reduces the amount of redundant data written to the storage system while maintaining inline data writing performance. Our experimental results show that HPDedup clearly outperforms the state-of-the-art primary storage deduplication techniques in terms of inline

关键词： Efficiency

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Audio Visual Speech Recognition with Multimodal Recurrent Neural Networks

Audio Visual Speech Recognition with Multimodal Recurrent Ne...

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International Joint Conference on Neural Networks

作者： Weijiang Feng Naiyang Guan Yuan Li Xiang Zhang Zhigang Luo Institute of Software College of Computer National University of Defense Technology Changsha Hunan P.R. China 410073 Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha Hunan P.R. China 410073

ISBN: (纸本)9781509061839

Studies on nowadays human-machine interface have demonstrated that visual information can enhance speech recognition accuracy especially in noisy environments. Deep learning has been widely used to tackle such audio visual speech recognition (AVSR) problem due to its astonishing achievements in both speech recognition and image recognition. Although existing deep learning models succeed to incorporate visual information into speech recognition, none of them simultaneously considers sequential characteristics of both audio and visual modalities. To overcome this deficiency, we proposed a multimodal recurrent neural network (multimodal RNN) model to take into account the sequential characteristics of both audio and visual modalities for AVSR. In particular, multimodal RNN includes three components, i.e., audio part, visual part, and fusion part, where the audio part and visual part capture the sequential characteristics of audio and visual modalities, respectively, and the fusion part combines the outputs of both modalities. Here we modelled the audio modality by using a LSTM RNN, and modelled the visual modality by using a convolutional neural network (CNN) plus a LSTM RNN, and combined both models by a multimodal layer in the fusion part. We validated the effectiveness of the proposed multimodal RNN model on a multi-speaker AVSR benchmark dataset termed AVletters. The experimental results show the performance improvements comparing to the known highest audio visual recognition accuracies on AVletters, and confirm the robustness of our multimodal RNN model.

关键词： Visualization Hidden Markov models Speech recognition Recurrent neural networks Feature extraction Logic gates Data models

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Pegasus：a distributed and load-balancing fingerprint identification system

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Frontiers of Information technology & Electronic Engineering 2016年第8期17卷 766-780页

作者： Yun-xiang ZHAO Wan-xin ZHANG Dong-sheng LI Zhen HUANG Min-ne LI Xi-cheng LU National Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha 410003 China

Fingerprint has been widely used in a variety of biometric identification systems in the past several years due to its uniqueness and immutability. With the rapid development of fingerprint identification techniques, many fingerprint identification systems are in urgent need to deal with large-scale fingerprint storage and high concurrent recognition queries, which bring huge challenges to the system. In this circumstance, we design and implement a distributed and load-balancing fingerprint identification system named Pegasus, which includes a distributed feature extraction subsystem and a distributed feature storage subsystem. The feature extraction procedure combines the Hadoop Image Processing Interface（HIPI） library to enhance its overall processing speed; the feature storage subsystem optimizes MongoD B＇s default load balance strategy to improve the efficiency and robustness of *** and simulations are carried out, and results show that Pegasus can reduce the time cost by 70% during the feature extraction procedure. Pegasus also balances the difference of access load among front-end mongos nodes to less than 5%. Additionally, Pegasus reduces over 40% of data migration among back-end data shards to obtain a more reasonable data distribution based on the operation load（insertion, deletion, update, and query） of each shard.

关键词： distributed fingerprint identification distributed MongoD B Load balancing

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An Energy Efficient Optimized Control Algorithm for Urban Rail Transit System 35

An Energy Efficient Optimized Control Algorithm for Urban Ra...

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第35届中国控制会议

作者： ZHANG Hongguang SONG Mengxiao ZHANG Minxuan College of Computer National University of Defense Technology College of Mechatronic Engineering and Automation National University of Defense Technology National Laboratory for Parallel and Distributed Processing National University of Defense Technology

ISBN: (纸本)9781509009107

The energy consumption of urban rail transit system involves train traction, air conditioning system, elevator, water supply and drainage equipment and so on, wherein the traction energy consumption accounts for more than 40% of the total energy consumption. With more concerning about low-carbon and environment protection, it has become a research hotspot that how to minimize the traction energy consumption during operation. Aiming at the optimized control of single train in complex line conditions, we design an algorithm based on recursion, by which we can obtain the most efficient control strategy with a set of constraints and effectively reduce the traction energy consumption. Meanwhile, we focus on the multiple-unit trains' cooperative control issue, and give the relevant solutions to improve the proportion of recovered renewable braking energy.

关键词： urban rail transit efficient algorithm recursion cooperative control

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An Efficient Label Routing on High-Radix Interconnection Networks

An Efficient Label Routing on High-Radix Interconnection Net...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Fei Lei Dezun Dong Xiangke Liao College of Computer National University of Defense Technology China National Laboratory for Parallel and Distributed Processing National University of Defense Technology China Collaborative Innovation Center of High Performance Computing National University of Defense Technology China

ISBN: (纸本)9781538632086

Cost-effective adaptive routing has a significant impact on overall performance for high-radix hierarchical topologies, such as Dragonfly, which achieve a lower network diameter than traditional topologies, Torus and Fat tree, but exhibit a lower degree of adaptiveness for shortest-path rout- ing. Existing adaptive routing methods for those hierarchical topologies improve the adaptiveness by increasing path length, i.e. local or global adaptive routing, and thus suffer from complex and costly deadlock avoidance. This work aims to maximize the routing adaptiveness at the minimum cost of deadlock avoidance. We propose a label routing method for high-radix hierarchical networks. This label routing utilizes a co-design methodology and coordinates the two pipelines, input queue and routing computation, in the router microarchitec- ture. Packets in the input buffer are labeled by our routing algorithm depending on network states. We reorganize the input buffer and develop a label routing algorithm, named Green-Red Routing, GRR. GRR relaxes the requirement of using virtual channels to eliminate routing deadlock, and mitigates buffer resources dedicated to deadlock avoidance. GRR manages the buffer resources and balance its utilization elaborately, and achieve fully adaptive routing efficiently. We conduct extensive experiments to evaluate the performance of GRR on Dragonfly and compare it with state-of-the-art works. The results show that GRR achieves 10%-35% higher performance than existing routing algorithms under most traffic patterns.

关键词： Routing System recovery Network topology Topology Resource management Adaptive systems Organizations

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A secure light-weight public auditing scheme in cloud computing with potentially malicious third party auditor

A secure light-weight public auditing scheme in cloud comput...

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作者： Wu, Yilun Lin, Xinye Lu, Xicheng Su, Jinshu Chen, Peixin College of Computer National University of Defense Technology China School of Computer Science McGill University Montreal Canada National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology China

Public auditing is a new technique to protect the integrity of outsourced data in the remote cloud. Users delegate the ability of auditing to a third party auditor (TPA), and assume that each result from the TPA is correct. However, the TPA is not always trustworthy in reality. In this paper, we consider a scenario in which the TPA may lower the reputation of the cloud server by cheating users, and propose a novel public auditing scheme to address this security issue. The analyses and the evaluation prove that our scheme is both secure and efficient. © 2016 The Institute of Electronics, Information and Communication Engineers.

关键词： Cloud security

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SinglA image super-resolution via classified sparse Representation 13

SinglA image super-resolution via classified sparse Represen...

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13th International Conference on Embedded Software and System, ICESS 2016

作者： Lai, Chao Li, Fangzhao Li, Bao Jin, Shiyao National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781509037261

Single image super-resolution reconstruction is a challenging ill-posed inverse problem currently. In this paper, we propose a method based on image classification and sparse representation for single image super-resolution reconstruction. Various images belong to different image category, and each category contains different contents and structures respectively, especially the high-frequency feature. Therefore, we extract the features of the input low-resolution image, and classify it into the corresponding category. Then the high-resolution image is reconstructed by sparse representation with the dictionary trained from the corresponding database, which consists of high-resolution and low-resolution image patch pairs. The experimental results demonstrate that our method achieves better performance in visual effect and qualitative analysis, by comparison with some well-known methods. © 2016 IEEE.

关键词： Image classification

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Flip-flops soft error rate evaluation approach considering internal single-event transient

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science China(Information sciences) 2015年第6期58卷 159-170页

作者： SONG RuiQiang CHEN ShuMing HE YiBai DU YanKang College of Computer Science National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory

The internal single-event transient(SET) induced upset in flip-flops is becoming significant with the increase of the operating frequency. However, the conventional soft error rate(SER) evaluation approach could only produce an approximate upset prediction result caused by the internal SET. In this paper, we propose an improved SER evaluation approach based on Monte Carlo simulation. A novel SET-based upset model is implemented in the proposed evaluation approach to accurately predict upsets caused by the internal SET. A test chip was fabricated in a commercial 65 nm bulk process to validate the accuracy of the improved SER evaluation approach. The predicted single-event upset cross-sections are consistent with the experimental data.

关键词： soft error rate Monte Carlo internal SET single-event upset flip-flops

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OpenMP 4.0 based heterogeneous parallel optimization of an engine combustion simulation application 2

OpenMP 4.0 based heterogeneous parallel optimization of an e...

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2nd IEEE International Conference on computer and Communications, ICCC 2016

作者： Meifang, Yang Che, Yonggang Gao, Xiang Science and Technology on Parallel and Distributed Processing Laboratory China School of Computer China National University of Defense Technology Changsha China School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781467390262

LESAP is a combustion simulation application capable of simulating the chemical reactions and supersonic flows in the scramjet engines. It can be used to solve practical engineering problems and involves a large amount of computations. In this paper, we port and optimize LESAP with the OpenMP 4.0 accelerator model, targeting the heterogeneous many-core platform composed of general CPU and Intel Many Integrated Core (MIC). Based on the application characteristics, a series of techniques are proposed, including OpenMP 4.0 based task offloading, data movement optimization, grid-partition based load-balancing and SIMD optimization. The performance evaluation is done for a real combustion simulation configuration, with 532,0896 grid cells, on one Tianhe-2 supercomputer node. The results show that the resulting heterogenous code significantly outperforms the original CPU only code. When the heterogenous code runs on two Intel Xeon E5-2692 CPUs and three Intel Xeon Phi 31S1P coprocessors, it achieves a maximum speedup of 3.63x over the original code that only runs on the two Intel Xeon E5-2692 CPUs. © 2016 IEEE.

关键词： Program processors

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