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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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Implementation of a Fine-Grained parallel full pipeline Schnorr–Euchner sphere decoder algorithm accelerator on Field-Programmable gate array 4th

Implementation of a Fine-Grained parallel full pipeline Schn...

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4th International Conference on Computer Engineering and Networks, CENet2014

作者： Li, Shijie Guo, Lei Dou, Yong Jiang, Jingfei National laboratory for parallel and distributed processing National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319111032

A new parallel full pipeline accelerator implemented on fieldprogrammable gate array (FPGA) for the Schnorr–Euchner sphere decoding (SE– SD) algorithm is presented in this paper. We firstly transform the serial SE–SD algorithm into a parallel one. Afterwards, we use multiple processing elements (PEs) to deal with the workload (particularly for tree searching in the SE–SD algorithm) in parallel. Each separated SE–SD search workload is divided averagely. Each PE searches a sub-tree by using a multilevel pipeline to increase the data throughput, and the whole system obtains a batch of different input data chronologically. We select the number of PEs to distribute our system according to the hardware platform by using a distribution unit. We’ve successfully placed four PEs in an accelerator and eight accelerators in a single FPGA (XC6VLX240T). The system obtains remarkable benefit in changing the accelerate mode, including latency- and throughput-prior modes. © Springer International Publishing Switzerland 2015.

关键词： MIMO systems

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Software ranking and analysis based on mining market requirements and characteristics 15

Software ranking and analysis based on mining market require...

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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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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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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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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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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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Poster: Segmentation Based Online Performance Problem Diagnosis 37

Poster: Segmentation Based Online Performance Problem Diagno...

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37th IEEE/ACM International Conference on Software Engineering, ICSE 2015

作者： Zhou, Jingwen Chen, Zhenbang Wang, Ji Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781479919345

Currently, the performance problems of software systems gets more and more attentions. Among various diagnosis methods based on system traces, principal component analysis (PCA) based methods are widely used due to the high accuracy of the diagnosis results and requiring no specific domain knowledge. However, according to our experiments, we have validated several shortcomings existed in PCA-based methods, including requiring traces with a same call sequence, inefficiency when the traces are long, and missing performance problems. To cope with these issues, we introduce a segmentation based online diagnosis method in this poster. © 2015 IEEE.

关键词： Principal component analysis

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A survey on concepts and the state of the art of functional programming languages

A survey on concepts and the state of the art of functional ...

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International Symposium on Systems and Computer technology, ISSCT 2014

作者： Jian, Song-lei Lu, Kai Wang, Xiao-ping Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781138028722

Functional programming languages have a long history and receive more and more attention today. The paper focuses on the development of functional languages and aims to introduce the concepts, such as higher-order functions, lazy evaluation, data type, and pattern matching. We also review the evolution of functional programming languages from lambda calculus, Lisp to Haskell. Based on the analysis of leading papers published on ACM conferences, we survey 5 active research areas: monads, verification, type system, data parallelism, and application of functional programming languages and discuss the limitation of functional programming languages. © 2015 Taylor & Francis Group, London.

关键词： Surveys

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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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