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15th International Conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

作者： Zhao, Yunxiang Zhang, Wanxin Li, Dongsheng Huang, Zhen National Laboratory for Parallel and Distributed Processing College of Computer National University of Defence Technology ChangshaHunan410073 China

ISBN: (纸本)9783319271361

Fingerprint has been widely used in a variety of biometric identification systems. However, with the rapid development of fingerprint identification systems, the amount of fingerprints information stored in systems has been rising sharply, making it challenging to process and store fingerprints efficiently and robustly with traditional standalone systems and relational databases. In this paper, we propose a scalable distributed fingerprint identification system, named DFIS. It combines the feature extraction procedure with HIPI library and optimizes the load balance strategy of MongoDB to construct a much more robust and stable system. Related experiments and simulations have been carried out and results show that DFIS can reduce the time expense by 70% during the features extraction procedural. For load balance of MongoDB, DFIS can decrease the difference of access load to less than 5% and meanwhile decrease 50% data migration to gain more reasonable distribution of operation load and data load among shards compared with the default load balance strategy in MongoDB. © Springer International Publishing Switzerland 2015.

关键词： distributed computer systems

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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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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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Identifying repeated interleavings to improve the efficiency of concurrency bug detection 15th

Identifying repeated interleavings to improve the efficiency...

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15th International Conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

作者： Wu, Zhendong Lu, Kai Wang, Xiaoping Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319271392

Detecting concurrency bugs is becoming increasingly important. Many pattern-based concurrency bug detectors focus on the specific types of interleavings that are correlated to concurrency bugs. To detect multiple types of concurrency bugs, general detectors focus on multiple types of interleaving patterns, including data race pattern, atomicity violation pattern, and atomic-set violation pattern. Unfortunately, they suffer from redundant analysis due to repeated interleavings, which may affect the efficiency of concurrency bug detection. Hence, we propose an approach to identify the repeated interleavings. To the best of our knowledge, this is the first approach that can prune repeated interleavings to improve the efficiency of concurrency bug detection. We apply our approach to existing general detectors (PECAN and Maple) to avoid analyzing repeated interleavings. We evaluated the general detectors with and without our approach, respectively. The experimental results show that the bug detection results are not affected. With our approach, the bug detection time of PECAN and Maple are reduced by 40.0% and 44.4%, respectively. Additionally, our approach does not affect the overhead of bug detection, and consumes only a little memory. © Springer International Publishing Switzerland 2015.

关键词： Efficiency

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Improving performance portability for GPU-specific Open CL kernels on multi-core/many-core CPUs by analysis-based transformations

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Frontiers of Information Technology & Electronic Engineering 2015年第11期16卷 899-916页

作者： Mei WEN Da-fei HUANG Chang-qing XUN Dong CHEN School of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Processing

OpenCL is an open heterogeneous programming framework. Although OpenCL programs are func- tionally portable, they do not provide performance portability, so code transformation often plays an irreplaceable role. When adapting GPU-specific OpenCL kernels to run on multi-core/many-core CPUs, coarsening the thread granularity is necessary and thus has been extensively used. However, locality concerns exposed in GPU-specific OpenCL code are usually inherited without analysis, which may give side-effects on the CPU performance. Typi- cally, the use of OpenCL＇s local memory on multi-core/many-core CPUs may lead to an opposite performance effect, because local-memory arrays no longer match well with the hardware and the associated synchronizations are costly. To solve this dilemma, we actively analyze the memory access patterns using array-access descriptors derived from GPU-specific kernels, which can thus be adapted for CPUs by （1） removing all the unwanted local-memory arrays together with the obsolete barrier statements and （2） optimizing the coalesced kernel code with vectorization and locality re-exploitation. Moreover, we have developed an automated tool chain that makes this transformation of GPU-specific OpenCL kernels into a CPU-friendly form, which is accompanied with a scheduler that forms a new OpenCL runtime. Experiments show that the automated transformation can improve OpenCL kernel performance on a multi-core CPU by an average factor of 3.24. Satisfactory performance improvements axe also achieved on Intel＇s many-integrated-core coprocessor. The resultant performance on both architectures is better than or comparable with the corresponding OpenMP performance.

关键词： OpenCL Performance portability Multi-core/many-core CPU Analysis-based transformation

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Cooperative repair based on tree structure for multiple failures in distributed storage systems with regenerating codes 15

Cooperative repair based on tree structure for multiple fail...

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12th ACM International Conference on Computing Frontiers, CF 2015

作者： Pei, Xiaoqiang Wang, Yijie Ma, Xingkong Fu, Yongquan Xu, Fangliang Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan410073 China

ISBN: (纸本)9781450333580

Regenerating codes have been proposed to achieve an optimal trade-off curve between the amount of storage space and the network traffic for repair. However, existing repair schemes based on regenerating codes are inadequate to meet the requirements of small network traffic cost and high efficiency when repairing multiple failures. In this paper, we propose a cooperative repair scheme based on tree structure for multiple failures with regenerating codes, called CTREE. For generality, we propose a two-layer repair framework to support both repairs for single and multiple failures. For high repair efficiency, a parallel tree-structured data transmission technique is proposed to organize the data transmissions between the providers and newcomers. For small network network traffic cost, a core-based data exchange technique is proposed to organize the data exchanges between the coordinator and the other newcomers. To evaluate the performance of CTREE, we conduct experiments on both 30 physical and 200 virtual servers. Numerical analysis and extensive experiments confirm that CTREE can support both single and multiple failure repairs, significantly reduces the network traffic cost and improves the repair efficiency compared with the state-of-the-art approaches under various parameter settings. © Copyright 2015 ACM.

关键词： Repair

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parallel pipeline implementation for moving objects detection in traffic video analysis on a heterogeneous platform 4th

Parallel pipeline implementation for moving objects detectio...

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4th International Conference on computer Engineering and Networks, CENet2014

作者： Li, Teng Dou, Yong Jiang, Jingfei Qiao, Peng Department of Computer Science National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319111032

Moving objects detection is important in traffic video analysis, and many algorithms are being increasingly applied to moving objects detection. Most of these algorithms are time-consuming and cannot satisfy real-time demand in traffic video analysis by using a conventional central processing unit (CPU) sequential method. The emergence of the graphics processing unit (GPU) and multi-core CPU provides a method to accelerate the aforementioned algorithms to meet demand. In this study, we provide a GPU-accelerated implementation of the background subtraction algorithm and the morphological operation algorithm. Then, the connected component labeling algorithm is parallelized on a multi-core CPU with Open Multi-processing (OpenMP). Furthermore, parallel pipeline implementation on a heterogeneous platform is proposed by integrating the aforementioned algorithms. Experimental results show that the proposed implementation achieves a significant speedup of up to 5×, compared with sequential implementation on a CPU. © Springer International Publishing Switzerland 2015.

关键词： Program processors

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Deadline-oriented task scheduling for mapreduce environments 15th

Deadline-oriented task scheduling for mapreduce environments

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15th International Conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

作者： Hu, Minghao Wang, Changjian You, Pengfei Huang, Zhen Peng, Yuxing National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410072 China

ISBN: (纸本)9783319271217

To provide timely results for ‘Big Data Analytics’, it is crucial to satisfy deadline requirements for MapReduce jobs in production environments. In this paper, we propose a deadline-oriented task scheduling approach, named Dart, to meet the given deadline and maximize the input size if only part of the dataset can be processed before the time limit. Dart uses an iterative estimation method which is based on both historical data and job running status to precisely estimate the realtime job completion time. By comparing the estimated time with the deadline constraint, a YARN-based task scheduler dynamically decides whether continuing or terminating the map *** have validated our approach using workloads from OpenCloud and Facebook on a cluster of 60 virtual machines. The results show that Dart can not only effectively meet the deadline but also process near-maximal data volumes even when the deadline is set to be extremely small and limited resources are allocated. © Springer International Publishing Switzerland 2015.

关键词： MapReduce

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Partial clones for stragglers in MapReduce

Partial clones for stragglers in MapReduce

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

作者： Li, Jia Wang, Changjian Li, Dongsheng Huang, Zhen National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783662462478

Stragglers can temporize jobs and reduce cluster efficiency seriously. Many researches have been contributed to the solution, such as Blacklist[8], speculative execution[1, 6], Dolly[8]. In this paper, we put forward a new approach for mitigating stragglers in MapReduce, name Hummer. It starts task clones only for high-risk delaying tasks. Related experiments have been carried and results show that it can decrease the job delaying risk with fewer resources consumption. For small jobs, Hummer also improves job completion time by 48% and 10% compared to LATE and Dolly. © Springer-Verlag Berlin Heidelberg 2015.

关键词： MapReduce

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