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

作者： Cang Liu Chuan Tang Zuocheng Xing Lirui Chen Yang Zhang Guitao Fu National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Beijing Satellite Navigation Center Beijing China

ISBN: (纸本)9781509032068

The QR decomposition (QRD) has been extensively adopted in the transceiver processor of Multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The antenna configuration of future MIMO-OFDM system is very flexible. Therefore, the QRD architecture should also has the flexibility feature to decompose various dimensional channel response matrices. However, the existing QRD hardware architectures for MIMO-OFDM systems mainly focus on several fixed dimensional matrices. Due to the flexibility and scalability of parallel tiled QRD algorithm, it is very suitable for future MIMO-OFDM systems. A versatile hardware architecture (Ver_Arch) is designed for the bottleneck operations of parallel tiled QRD algorithm in this paper. Based on the designed Ver_Arch, we also design a QRD architecture for 4×4 real matrix. To the best of our knowledge, this is the first paper that presents a completed QRD hardware architecture based on the parallel tiled QRD algorithm for MIMO-OFDM wireless communication systems.

关键词： Matrix decomposition Hardware Algorithm design and analysis Computer architecture Wireless communication MIMO OFDM

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Maximizing Uniform Multicast Throughput in Multi-Channel Dense Wireless Sensor Networks 12

Maximizing Uniform Multicast Throughput in Multi-Channel Den...

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12th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2016

作者： Jiao, Xianlong Chen, Guirong Wang, Xiaodong Chen, Yuli Yang, Li Information and Navigation College Air Force Engineering University Xi'an710077 China College of Information System and Management National University of Defense Technology Changsha410073 China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China Chongqing Guanyinqiao Elementary School Chongqing400020 China Chongqing Liangjiangxinqu Renhe Experimental School Chongqing400021 China

ISBN: (纸本)9781509056965

This paper investigates the problem of maximizing uniform multicast throughput (MUMT) for multi-channel dense wireless sensor networks, where all nodes locate within one-hop transmission range and can communicate with each other on multiple orthogonal channels. This kind of networks show wide application in the real world, and maximizing uniform multicast throughput for these networks is worth deep studying. Previous researches have proved MUMT problem is NP-hard. However, previous researches are either hard to implement, or use too many relay nodes to complete the multicast task, and thus incur high overhead or poor performance. To efficiently solve MUMT problem, we adopt the concept of the maximum independent set with the size constraint, and present one novel Single-Broadcast based Multicast algorithm called SBM based on the concept. We prove that SBM algorithm achieves a constant ratio to the theoretical throughput upper bound. Extensive experimental results demonstrate that, SBM performs better than existing work in terms of both the uniform multicast throughput and the total number of transmissions. © 2016 IEEE.

关键词： Throughput

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DIPP—An LLC replacement policy for on-chip dynamic heterogeneous multi-core architecture

DIPP—An LLC replacement policy for on-chip dynamic heteroge...

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International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2015

作者： Yang, Zhang Zuocheng, Xing Xiao, Ma Science and technology on Parallel and distributed processing laboratory National University of Defense Technology ChangSha China

ISBN: (纸本)9783662462478

As the big data era is coming, it brings new challenges to the massive data processing. A combination of GPU and CPU on chip is the trend to release the pressure of large scale computing. We found that there are different memory access characteristics between GPU and CPU. The most important one is that the programs of GPU include a large number of threads, which lead to higher access frequency in cache than the CPU programs. Although the LRU policy favors the programs with high memory access frequency, the programs of GPU can’t get the corresponding performance boost even more cache resources are provided. So LRU policy is not suitable for heterogeneous multi-core processor. Based on the different characteristics of GPU and CPU programs on memory access, this paper proposes an LLC dynamic replacement policy--DIPP (Dynamic Insertion/ Promotion Policy) for heterogeneous multi-core processors. The core idea of the replacement policy is to reduce the miss rate of the program and enhance the overall system performance by limiting the cache resources that GPU can acquire and reducing the thread interferences between programs. Experiments compare the DIPP replacement policy with LRU and we conduct a classified discussion according to the program results of GPU. Friendly programs enhance 23.29% on the average performance (using arithmetic mean). Large working sets programs can improve 13.95%, compute-intensive programs enhance 9.66% and stream class programs improve 3.8%. © Springer-Verlag Berlin Heidelberg 2015.

关键词： Graphics processing unit

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Enhancing Temporal Alignment with Autoencoder Regularization

Enhancing Temporal Alignment with Autoencoder Regularization

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International Joint Conference on Neural Networks

作者： Liquan Nie Yuanyuan Wang Xiang Zhang Xuhui Huang Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Department of Basic Courses Army Officer Academy Department of Computer Science and Technology College of Computer National University of Defense Technology

ISBN: (纸本)9781509006212

Temporal alignment aligns two temporal sequences and is quite challenging due to drastic differences among temporal sequences and source data from different views. Canonical time warping (CTW) has shown great potential in temporal alignment tasks because it can reduce data redundancy by transforming high-dimensional data to a lower-dimensional subspace via canonical correlation analysis (CCA). However, CTW cannot uncover the underlying nonlinear structure embedded in the dataset. In this paper, we propose an autoencoder regularized canonical time warping method (AECTW) to overcome this drawback. Specifically, AECTW enhances lower-dimensional representation of each sequence by incorporating an autoencoder regularization, meanwhile reveals the nonlinear structure of features by explicit nonlinear transformation. By these strategies, AECTW significantly boosts CTW in temporal alignment tasks. Experiments on both synthetic data and two practical human action datasets demonstrate that AECTW outperforms the representative DTW-based methods.

关键词： NONLINEAR STRUCTURES data redundancy Dataset synthetic data Alignment Warping Structural properties Canonical Religious Missions Data sources

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A data-driven mechanism for large-scale data distribution

A data-driven mechanism for large-scale data distribution

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Proceedings of the Biannual World Automation Congress

作者： Peichang Shi Yiying Li Bo Ding Longquan Jiang Hui Liu Jie Zhang National Key Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha Hunan CN National Key Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 China National University of Defense Technology Changsha Hunan CN China Electr. Equip. & Syst. Eng. Co. Ltd. China

As The integration of Physical space and cyberspace, the large-scale data distributing to diversification terminal which is geographical distribution of mass has become a huge challenge. When the data size can't be processed by the technology for traditional scope, how to deal with the user quality of service and efficient use of system resources has become an important issue of concern, with the resources becoming limited. This paper presents a data-driven mechanism for large-scale data distribution which is consists of four core part of the data production, data collection and pre-processing, data analysis engine, data consumption, aims to excavate the valuable information to improve the efficiency of resource use and accurate fault location for the Large-scale data distribution system. At the same time, this paper studies the resource scheduling optimization with analyzing data driven for the system behavior and Fault location with analyzing data-driven environment, which proves the effectiveness for the operation of the Large-scale data distribution system optimization by the data-driven working.

关键词： Servers Monitoring distributed databases Big data Real-time systems Business

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Tendency-based caching in Content-Centric Networking

Tendency-based caching in Content-Centric Networking

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International Conference on Ubiquitous and Future Networks, ICUFN

作者： YuSheng Xia YaPing Liu JinShu Su College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467399920

In content-centric networking, the schemes of innetwork caching can affect the performance of the whole network. Existing schemes lack of the global view, which results in inefficient caches. In this paper, we aim to analyze the real-time distribution of contents among caches from multiple perspectives. This paper proposes TCBRP, a scheme that analyzes caching tendency of various contents in reverse path, based on centrality of nodes, popularity of contents and replacement rate of nodes, to cache in-network contents. This scheme also has decent scalability and can be expended conveniently. The experimental results reflect that TCBRP report savings in average hops and balance cache hit rate, compared with BetwRep and LCE.

关键词： Probability Internet Network architecture Mathematical model Statistical analysis Correlation Fading channels

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Airport Detection from Remote Sensing Images Using Transferable Convolutional Neural Networks

Airport Detection from Remote Sensing Images Using Transfera...

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International Joint Conference on Neural Networks

作者： Peng Zhang Xin Niu Yong Dou Fei Xia National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Electronic Engineering College Navy Engineering University Wuhan China

ISBN: (纸本)9781509006212

This paper presents a method for airport detection from optical satellite images using deep convolutional neural networks (CNN). To achieve fast detection with high accuracy, region proposal by searching adjacent parallel line segments has been applied to select candidate fields with potential runways. These proposals were further classified by a CNN model transfer learned from AlexNet to identify the final airport regions from other confusing classes. The proposed method has been tested on a remote sensing dataset consisting of 120 airports. Experiments showed that the proposed method could recognize airports from a large complex area in seconds with an accuracy of 84.1%.

关键词： Airports Proposals Remote sensing Image segmentation Feature extraction Atmospheric modeling Joining processes

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High Performance Interconnect Network for Tianhe System

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Journal of Computer science & technology 2015年第2期30卷 259-272页

作者：廖湘科庞征王克非卢宇彤谢旻夏军董德尊所光 College of Computer National University of Defense Technology Changsha 410073 Science and Technology on Parallel and Distributed Processing Laboratory National Changsha 410073 China China University of Defense Technology State Key Laboratory of High Performance Computing National University of Defense Technology Changsha 410073 China

In this paper, we present the Tianhe-2 interconnect network and message passing services. We describe the architecture of the router and network interface chips, and highlight a set of hardware and software features effectively supporting high performance communications, ranging over remote direct memory access, collective optimization, hardwareenable reliable end-to-end communication, user-level message passing services, etc. Measured hardware performance results are also presented.

关键词： Tianhe-2 supercomputer interconnect network router architecture network interface architecture user-level message passing

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Labelwalking nonnegative matrix factorization 40

Labelwalking nonnegative matrix factorization

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40th IEEE International Conference on Acoustics, Speech, and Signal processing, ICASSP 2015

作者： Lan, Long Guan, Naiyang Zhang, Xiang Huang, Xuhui Luo, Zhigang Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781467369978

Semi-supervised learning (SSL) utilizes plenty of unlabeled examples to boost the performance of learning from limited labeled examples. Due to its great discriminant power, SSL has been widely applied to various real-world tasks such as information retrieval, pattern recognition, and speech separa- tion. Label propagation (LP) is a popular SSL method which propagates labels through the dataset along high density areas defined by unlabeled examples, LP assumes nearby examples should share the same label, thus, it unavoidably pushes the labels to the wrong examples, especially when different la- beled examples are not strictly separated. Seed K-means uses labeled examples to initialize class centers, and avoid getting stuck in poor local optima comparing to traditional K-means, however the hard constraint of each example's membership makes Seed K-means failed in many real world applications. This paper proposes a novel label walking nonnegative matrix factorization method (LWNMF) to handle labeled examples in SSL based on the framework of NMF. LWNMF decomposes the whole dataset into the product of a basis matrix and a coefficient matrix, and to travel labels to unlabeled examples, LWNMF regards the class indicators of labeled examples as their coefficients and iteratively updates both basis matrix and coefficients of unlabeled examples. Since LWNMF learns comprehensive class centroids, labels iteratively walk to unlabeled examples through these significant centroids. © 2015 IEEE.

关键词： K-means Label propagation Nonnegative matrix factorization Semisupervised learning

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An Efficient and Flexible Deterministic Framework for Multithreaded Programs

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Journal of Computer science & technology 2015年第1期30卷 42-56页

作者：卢凯周旭王小平 Tom Bergan 陈沉 Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China College of Computer National University of Defense Technology Changsha 410073 China Department of Computer Science and Engineering University of Washington Seattle WA 98195-2350 U.S.A.

Determinism is very useful to multithreaded programs in debugging, testing, etc. Many deterministic ap- proaches have been proposed, such as deterministic multithreading （DMT） and deterministic replay. However, these sys- tems either are inefficient or target a single purpose, which is not flexible. In this paper, we propose an efficient and flexible deterministic framework for multithreaded programs. Our framework implements determinism in two steps： relaxed determinism and strong determinism. Relaxed determinism solves data races eificiently by using a proper weak memory consistency model. After that, we implement strong determinism by solving lock contentions deterministically. Since we can apply different approaches for these two steps independently, our framework provides a spectrum of deterministic choices, including nondeterministic system （fast）, weak deterministic system （fast and conditionally deterministic）, DMT system, and deternfinistic replay system. Our evaluation shows that the DMT configuration of this framework could even outperform a state-of-the-art DMT system.

关键词： determinism multithreading framework flexible

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