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7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Liu, Bingxun Yin, Gang Wang, Tao Zhang, Fang Wang, Huaimin National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

As the rapid growth of open source software, how to choose software from many alternatives becomes a great challenge. Traditional ranking approaches mainly focus on the characteristics of the software themselves, such as qualities, security, reliable and so on. In this paper we investigate the market demands for software engineers, and propose a novel approach for ranking software by analyzing the market requirements for special software. At the same time we conclude the characteristics of software advertisements and analyze the reasons that why these situations emerge and tendency of software market requirements. As industries always need to balance several different factors for selecting software, the market demands can be a good indicator for ranking software and software evaluating. This paper provides quite a different perspective and some interesting inferences on software market requirements, and it can be a valuable supplement for traditional ranking methods, as well as software evaluating. © 2015 ACM.

关键词： Open source software

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Enabling Tissue-Scale Cardiac Simulations Using Heterogeneous Computing on Tianhe-2

Enabling Tissue-Scale Cardiac Simulations Using Heterogeneou...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Johannes Langguth Qiang Lan Namit Gaur Xing Cai Mei Wen Chun-Yuan Zhang Simula Research Laboratory Lysaker Norway College of Computer National University of Defense Technology Changsha China National Key Laboratory of Parallel and Distributed Processing Changsha China Department of Informatics University of Oslo Oslo Norway

ISBN: (纸本)9781509053827

We develop a simulator for 3D tissue of the human cardiac ventricle with a physiologically realistic cell model and deploy it on the supercomputer Tianhe-2. In order to attain the full performance of the heterogeneous CPU-Xeon Phi design, we use carefully optimized codes for both devices and combine them to obtain suitable load balancing. Using a large number of nodes, we are able to perform tissue-scale simulations of the electrical activity and calcium handling in millions of cells, at a level of detail that tracks the states of trillions of ryanodine receptors. We can thus simulate arrythmogenic spiral waves and other complex arrhythmogenic patterns which arise from calcium handling deficiencies in human cardiac ventricle tissue. Due to extensive code tuning and parallelization via OpenMP, MPI, and SCIF/COI, large scale simulations of 10 heartbeats can be performed in a matter of hours. Test results indicate excellent scalability, thus paving the way for detailed whole-heart simulations in future generations of leadership class supercomputers.

关键词： Calcium Computational modeling Mathematical model Performance evaluation Hardware Instruction sets Supercomputers

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Locality Protected Dynamic Cache Allocation Scheme on GPUs

Locality Protected Dynamic Cache Allocation Scheme on GPUs

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

作者： Yang Zhang Zuocheng Xing Li Zhou Chunsheng Zhu National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China School of Electronic Science and Engineering National University of Defense Technology Changsha China Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada

ISBN: (纸本)9781509032068

As we are approaching the exascale era in supercomputing, designing a balanced computer system with powerful computing ability and low energy consumption becomes increasingly important. GPU is a widely used accelerator in most recently applied supercomputers. It adopts massive multithreads to hide long latency and has high energy efficiency. In contrast to its strong computing power, GPUs have few on-chip resources with several MB of fast on-chip memory storage per SM (Streaming Multiprocessors). GPU caches exhibit poor efficiency due to the mismatch of the throughput-oriented execution model and its cache hierarchy design. Since the severe deficiency in on-chip memory, the benefit of high computing capacity of GPUs is pulled down by the poor cache performance dramatically, which limits system performance and energy-efficiency. In this paper, we put forward a locality protected scheme to make full use of the data locality based on the fixed capacity. We present a Locality Protected method based on instruction PC (LPP) to promote GPU performance. Firstly, we use a PC-based collector to collect the reuse information of each cache line. After getting the dynamic reuse information of the cache line, we take an intelligent cache allocation unit (ICAU) which coordinates the reuse information with LRU (Least Recently Used) replacement policy to find out the cache line with the least locality for eviction. The results show that LPP provides an up to 17.8% speedup and an average of 5.5% improvement over the baseline method.

关键词： Graphics processing units System-on-chip computer architecture Instruction sets Resource management Optimization Electronic mail

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An Efficient Algorithm for Tensor Principal Component Analysis via Proximal Linearized Alternating Direction Method of Multipliers

An Efficient Algorithm for Tensor Principal Component Analys...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Linbo Qiao Bofeng Zhang Lei Zhuang Jinshu Su College of Computer National University of Defense Technology ChanzSha China National Laboratory for Parallel and Distributed Processing National University of Defense Technology ChangSha China Department of Statistics Shanghai University of Finance and Economics Shanghai China

ISBN: (纸本)9781509036783

In paper, we focus on the computation of the principal components for a general tensor, known as the tensor principal component analysis (PCA) problem. It has been proven that the general tensor PCA problem is reducible to its matricization form when the order is even. Usually it is considered as low-rank matrix completion problems theoretically. It is common to consider nuclear norm as a surrogate of the rank operator since it is the tightest convex lower bound of the rank operator under certain condition. However, most nuclear norm minimization based approaches involve numbers of singular value decomposition (SVD) operations. Given a matrix X ∈ R m × n , the time complexity of SVD operation is O(mn 2 ), which brings prohibitive computational burden to apply these methods in real applications. However, the problem is non-convex, and the proximal mapping associated with non-convex regularization is not easy to compute. It is always solved by the Linearized Alternating Direction Method of Multipliers (LADMM). Despite the success of LADMM in practice, it remains unknown if LADMM is convergent in solving such non-convex compositely regularized optimization. In this paper, we firstly present a detailed convergence analysis of the LADMM algorithm for solving non-convex compositely regularized optimization with a large class of non-convex penalties. Furthermore, we propose a new efficient and scalable algorithm for matrix principal component analysis called Proximal Linearized Alternating Direction Method of Multipliers for Principal Component Analysis(PLADMPCA). Different from traditional matrix factorization methods, PLADMPCA utilizes the linearization technique to formulate the matrix as an outer product of vectors, which greatly improves the computational efficacy compared to matrix factorization method. We empirically evaluate the proposed algorithm PLADMPCA on synthetic tensor data with different order. Results have shown that PLADMPCA have much better computational

关键词： Tensile stress Principal component analysis Algorithm design and analysis Convergence Matrix decomposition Optimization Computational efficiency

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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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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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DFIS: A scalable distributed fingerprint identification system 15th

DFIS: A scalable distributed fingerprint identification syst...

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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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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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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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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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