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检索条件"任意字段=10th IFIP International Conference on Network and Parallel Computing, NPC 2013"

共 71 条记录，以下是51-60 订阅

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Visualization of Strong Ground Motion from the 2011 Off Tohoku, Japan (Mw=9.0) Earthquake Obtained from Dense Nation-Wide Seismic network and Large-Scale parallel FDM Simulation 1

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10th international conference on High Performance computing for Computational Science (VECPAR)

作者： Furumura, Takashi Univ Tokyo Ctr Integrated Disaster Informat Res Interfac Initiat Informat Studies Bunkyo Ku Tokyo 1130032 Japan

ISBN: (数字)9783642387180

ISBN: (纸本)9783642387180;9783642387173

Strong ground motion from the 2011 off Tohoku, Japan (Mw=9.0) earthquake is demonstrated by high-resolution 3D parallel FDM simulation of seismic wave propagation using the Earth Simulator supercomputer. Complicated wavefield accompanying the earthquake in connection with the radiation of seismic wave from complex source rupture process and strong amplification of ground motion in complicated subsurface structure beneath populated cities are demonstrated by the comparison of visualized seismic wavefield derived by the computer simulation and observation from dense nation-wide seismic network. Good correspondence between simulation results and observed actual seismic wavefield promising us the effectiveness of the present simulation model for ground motion simulation which is applicable not only for reproducing strong ground motions for the past events but also for mitigating earthquake disasters associated with future earthquakes.

关键词： FDM simulation 2011 off Tohoku Japan earthquake Earth Simulator parallel computing

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Towards Adapting parallel Programs to Different Platforms: Identifying Interaction Patterns

Towards Adapting Parallel Programs to Different Platforms: I...

引用

IEEE international conference on High Performance computing and Communications (HPCC)

作者： Bogdan Florin Cornea Jaroslaw Slawinski Julien Bourgeois Vaidy Sunderam Emory University Atlanta GA US FEMTO-ST Inst. UFC Besançon France

Modern parallel computing platforms exhibit substantial variation in communication performance between on-socket, on-node and inter-rack locations. When application interaction patterns are irregular, communication-aware process placement on such platforms can be critical for overall runtime. Understanding program interaction patterns can be valuable in order to minimize the impact of capacity variations in communications parameters. Such knowledge can also be useful in selecting the best execution platform from the available options. In this paper we propose an approach based on source code analysis which identifies parallel application communication patterns such as star, ring, mesh, or torus. Our implementation based on ROSE framework was tested on various parallel programs that exhibit different communication patterns. We present the accuracy as well as the limitations of our static identification approach. We envisage augmenting our approach with trace information from pilot runs and best effort approaches to determine a process interaction graph.

关键词： Topology network topology parallel processing Computer architecture Blood vessels Runtime Object recognition

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QbDJ: A Novel Framework for Handling Skew in parallel Join Processing on Distributed Memory

QbDJ: A Novel Framework for Handling Skew in Parallel Join P...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Long Cheng Spyros Kotoulas Tomas E. Ward Georgios theodoropoulos National University of Ireland Maynooth Ireland IBM Res. Dublin Ireland Durham University UK

the performance of parallel distributed data management systems becomes increasingly important with the rise of Big Data. parallel joins have been widely studied both in the parallel processing and the database communities. Nevertheless, most of the algorithms so far developed do not consider the data skew, which naturally exists in various applications. State of the art methods designed to handle this problem are based on extensions to either of the two prevalent conventional approaches to parallel joins - the hash-based and duplication-based frameworks. In this paper, we introduce a novel parallel join framework, query-based distributed join (QbDJ), for handling data skew on distributed architectures. Further, we present an efficient implementation of the method based on the asynchronous partitioned global address space (APGAS) parallel programming model. We evaluate the performance of our approach on a cluster of 192 cores (16 nodes) and datasets of 1 billion tuples with different skews. the results show that the method is scalable, and also runs faster with less network communication compared to state-of-art PRPD approach in [1] under high data skew.

关键词： Arrays Distributed databases Histograms parallel processing Instruction sets Probes Silicon

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A Comparative Study of Preconditioners for GPU-Accelerated Conjugate Gradient Solver

A Comparative Study of Preconditioners for GPU-Accelerated C...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Yao Chen Yonghua Zhao Wei Zhao Lian Zhao Computer Network Information Center University of Chinese Academy of Sciences Beijing China Computer Network Information Center Chinese Academy of Sciences Beijing China

We compare two types of preconditioners for GPU-Accelerated conjugate gradient solver. For the standard IC preconditioner, we exploit level scheduling to increase multi-thread parallelism of sparse triangular solve on GPU. Meanwhile, we propose a novel reordering technique to maximize the coalescing of global memory accesses. For the approximate inverse preconditioner SSOR-AI, we extend it to second order approximation. Experiments indicate that our IC PCG runs 25% faster than using vendor implementation in CUSPARSE library and SSOR-AI PCG can be twice as fast as IC PCG.

关键词： Graphics processing units Sparse matrices Optimization Integrated circuits Approximation methods parallel processing Linear systems

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Vehicle Tracking with Non-overlapping Views for Multi-camera Surveillance System

Vehicle Tracking with Non-overlapping Views for Multi-camera...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Wenbin Jiang Chang Xiao Hai Jin Shuo Zhu Zhiwei Lu Services Computing Technology and System Lab Cluster and Grid Computing Huazhong University of Science and Technology Wuhan China

With the rapid development of intelligent video surveillance system for transportation, traditional single-camera-based video analysis has become insufficient. Many researches have focused on the non-overlapping multi-camera target tracking. However, the tracking precision and the computing overhead are still big obstacles. this paper proposes a novel vehicle tracking approach for non-overlapping multi-camera targets with data fusion by using minimum cost and maximum flow method. Structured information of moving targets is extracted and associated with other information such as motion time, the topology of camera network to solve targeted vehicle tracks. Besides, to improve the performance of the process, a parallelization algorithm for camera network topology partitioning is presented, which makes it possible for each sub-graph to track target independently in parallel. the experiment results show that the presented approach is able to perform target vehicle tracking analysis with high efficiency and accuracy.

关键词： Cameras Target tracking Vehicles Feature extraction network topology Topology

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Design of Cloud-Based parallel Exclusive Signature Matching Model in Intrusion Detection

Design of Cloud-Based Parallel Exclusive Signature Matching ...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Yuxin Meng Wenjuan Li Lam-For Kwok Department of Computer Science City University of Hong Kong Hong Kong SAR China

Signature-based intrusion detection systems have been widely deployed in current network environments to defend against various attacks, but the expensive process of signature matching is a major suffering problem for these detection systems. thus, a high-performance signature matching scheme is of great importance for a signature-based IDS. In our previous work, we have developed an exclusive signature matching scheme that aims to identify a mismatch instead of locating an accurate match and achieved good results in the experiments. With the advent of Cloud computing, IDS as a service (IDSaaS) has been proposed as an alternative by offloading the expensive operations such as the process of signature matching to the cloud. In this paper, we attempt to design a parallel model to conduct the exclusive signature matching in a cloud. In the evaluation, we implemented our model in a cloud environment and investigated its performance compared with Snort. the experimental results indicate that our proposed model can achieve promising performance in such a cloud environment.

关键词： Cloud computing Computational modeling Payloads Intrusion detection Pattern matching Graphics processing units throughput

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MyCloud: On-Demand Virtual Cluster Provisioning on HPC Resources

MyCloud: On-Demand Virtual Cluster Provisioning on HPC Resou...

引用

IEEE international conference on High Performance computing and Communications (HPCC)

作者： Min Li Xin Yang Ze Yu Xiaolin Li Scalable Software Systems Laboratory University of Florida Gainesville Florida

Advances in the industry are gaining attentions from the scientific computing community. Programming models and frameworks such as MapReduce and Hadoop are attracting scientists due to their easy-to-use interfaces and autonomic parallel processing abilities. Compared with the conventional HPC execution environments, clouds possess desirable features such as administrative privilege, customizable software environments, and are more capable of supporting new frameworks and boosting inter-organization collaborations. Isolated private clouds and public clouds are used by scientists. However, extra administrative and monetary costs are inevitable in both cases. In this paper, we propose My Cloud, a resource management framework integrating cloud-based techniques into HPC systems. My Cloud supports both conventional HPC jobs and cloud-like on-demand virtual cluster provisioning on the same HPC cluster simultaneously. Dynamic resource sharing between the two environments is beneficial for cluster utilization and burst usages handling. the design of My Cloud is friendly to the state-of-the-art Software Defined networking technologies and opens opportunities for fine-grained application-aware network engineering.

关键词： Torque Cloud computing Resource management Program processors Servers Quantum computing

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Arbor: Efficient Large-Scale Graph Data computing Model

Arbor: Efficient Large-Scale Graph Data Computing Model

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Wei Zhou Bo Li Jizhong Han Zhiyong Xu Institute of Information Engineering Chinese Academy of Sciences Beijing China Department of Math and Computer Science Suffolk University Boston MA

Graph data is the default data organization mechanism used in large-scale Social network Service (SNS) applications. Traditional graph data computing models are used to dig out useful hidden information inside the data. However, the ever growing data volume is adding more and more pressures. To retrieve and discover the information, the system has to introduce a larger number of data iterations. this makes the data analysis operations becoming slower. To speed up these operations on large-scale graph data, recent research works focus on developing efficient parallel iteration processing strategies. However, the synchronization requirements between successive iterations can severely jeopardize the effectiveness of parallel operations. In this paper, we propose a novel large-scale graph data processing model, Arbor, to address these issues. Arbor substitutes time-constrained synchronization operations with nontime-constrained control message transmissions to increase the degree of parallelism. Furthermore, it develops a new graph data organization format, which can not only save storage space, but also accelerate graph data processing operations. We compare Arbor with other graph processing models using a large-scale experimental graph data, and the results show that it outperforms the state-of-the-art systems.

关键词： Data models Data analysis Synchronization Computational modeling Organizations Time factors

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Random Walk Based Inverse Influence Research in Online Social networks

Random Walk Based Inverse Influence Research in Online Socia...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Zhaoyan Jin Quanyuan Wu Dianxi Shi Huining Yan National Key Laboratory for Parallel and Distributed Processing NUDT Changsha Hunan P.R.China

ISBN: (纸本)9781479909735

In online social networks, social influence of a user reflects his or her reputation or importance in the whole network or to a personalized user. Social influence analysis can be used in many real applications, such as link prediction, friend recommendation and personalized searching. Personalized Page Rank, which ranks nodes according to the probabilities that a random walk starting from a personalized node stops at all nodes, is one of the most popular metrics for influence analysis. In this paper, we study the problem of inverse influence in online social networks. Different from Personalized Page Rank, the inverse influence for a personalized node ranks nodes according to the probabilities that all nodes stop at the personalized node in limited steps. We propose two computation models for inverse influence, i.e., the random walk based and the path based. Both of the models have high computation complexity, and cannot be used in large graphs, so we propose a Monte Carlo based approximation algorithm. Experiments from synthetic and real world datasets show that, our algorithm has equivalent or even better accuracy than related researches in link prediction, and thus can be used in friend recommendation in online social networks.

关键词： Prediction algorithms Social network services Equations Mathematical model Accuracy Approximation algorithms Measurement

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A Data Gathering Scheme for WSN/WSAN Based on Partitioning Algorithm and Mobile Sinks

A Data Gathering Scheme for WSN/WSAN Based on Partitioning A...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Xiangli Zhang Hanrong Bao Jin Ye Kun Yan Hongmei Zhang School of information and communication Guilin University of Electronic Technology Guilin China Computer and Electronic Information College Guangxi University Nanning China

ISBN: (纸本)9781479909735

Gathering data from sensors, mobile sink has been adopted in wireless sensor networks (WSN) and wireless sensor and actor network(WSAN) to achieve higher efficiency. With the help of mobile sink, sensors could attain a much longer lifetime than the past. However, mobile sink introduces new challenges such as large data gathering latency to WSN/WSAN. A lot of research efforts have been devoted to reduce the data gathering time. Cooperated with a novel partition algorithm, a concise and efficient data gathering scheme is proposed here. A given area can be divided into several zones with balanced data gathering latency. By modeling the partitioning problem as a Traveling Salesman Problem (TSP), an algorithm is designed to balance the data gathering latency among all the zones. then mobile sinks are assigned to these zones separately. the data could be gathered by these mobile sinks parallel thereupon. Extensive simulations are carried out to evaluate our proposed data gathering scheme. Different distribution patterns are considered. Effectiveness of our proposed data gathering scheme is proved by the simulation results.

关键词： Mobile communication Partitioning algorithms Sensors Wireless sensor networks Algorithm design and analysis Mobile computing Traveling salesman problems

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