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检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

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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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15th IEEE international conference on High Performance Computing and Communications (HPCC) /11th IEEE/IFIP international conference on Embedded and Ubiquitous Computing (EUC)

作者： Cheng, Long Kotoulas, Spyros Ward, Tomas E. Theodoropoulos, Georgios Natl Univ Ireland Maynooth Kildare Ireland IBM Res Dublin Ireland Univ Durham Durham DH1 3HP England

ISBN: (纸本)9780769550886

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： distributed join parallel join data skew high performance X10

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A distributed Vertex-Centric Approach for Pattern Matching in Massive Graphs

A Distributed Vertex-Centric Approach for Pattern Matching i...

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IEEE international conference on Big Data (Big Data)

作者： Fard, Arash Nisar, M. Usman Ramaswamy, Lakshmish Miller, John A. Saltz, Matthew Univ Georgia Dept Comp Sci Athens GA 30602 USA

ISBN: (纸本)9781479912926;9781479912933

Graph pattern matching is fundamentally important to many applications such as analyzing hyper-links in the World Wide Web, mining associations in online social networks, and substructure search in biochemistry. Most existing graph pattern matching algorithms are highly computation intensive, and do not scale to extremely large graphs that characterize many emerging applications. In recent years, graph processing frameworks such as Pregel have sought to harness shared nothing clusters for processing massive graphs through a vertex-centric, Bulk Synchronous parallel (BSP) programming model. However, developing scalable and efficient BSP-based algorithms for pattern matching is very challenging because this problem does not naturally align with a vertex-centric programming paradigm. This paper presents novel distributed algorithms based on the vertex-centric programming paradigm for a set of pattern matching models, namely, graph simulation, dual simulation and strong simulation. Our algorithms are fine-tuned to consider the challenges of pattern matching on massive data graphs. Furthermore, we introduce a new pattern matching model, called strict simulation, which outperforms strong simulation in terms of scalability while preserving its important properties. We investigate potential performance bottlenecks and propose several techniques to mitigate them. This paper also presents an extensive set of experiments involving massive graphs (millions of vertices and billions of edges) to study the effects of various parameters on the scalability and performance of the proposed algorithms. The results demonstrate that our techniques are highly effective in alleviating performance bottlenecks and yield significant scalability benefits.

关键词： data-intensive computing query graphs distributed algorithms graph simulation subgraph isomorphism

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A feasibility study on developing IoT/M2M applications over ETSI M2M architecture

A feasibility study on developing IoT/M2M applications over ...

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2013 19th IEEE international conference on parallel and distributed Systems, ICPADS 2013

作者： Lin, Fuchun Joseph Ren, Yi Cerritos, Eduardo College of Computer Science National Chiao Tung University 1001 Ta Hsueh Rd. Hsinchu 300 Taiwan

ISBN: (纸本)9781479920815

A common service platform is considered as the key enabler to catalyze the development of IoT/M2M applications for a large variety of vertical markets such as smart energy, smart transportation, home and industry automation, eHealth and connected vehicles. This paper reports an initial effort at National Chiao Tung University in Taiwan with such an experimental approach. We first train our graduate students with an ETSI M2M architecture-compliant service platform OpenMTC from FOKUS, and then charter them with the tasks of developing diverse M2M applications. The effort is used as a feasibility study to investigate how useful the notion of a common service platform for IoT/M2M is and how urgent an international standard is required in defining such a platform. We intend to use the result of the study to create a suitable IoT/M2M curriculum for our students. © 2013 IEEE.

关键词： Students

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distributed OPTIMIZATION VIA ADAPTIVE REGULARIZATION FOR LARGE PROBLEMS WITH SEPARABLE CONSTRAINTS

DISTRIBUTED OPTIMIZATION VIA ADAPTIVE REGULARIZATION FOR LAR...

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IEEE international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Gilboa, Elad Chavali, Phani Yang, Peng Nehorai, Arye Washington Univ Preston M Green Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781479903566

Many practical applications require solving an optimization over large and high-dimensional data sets, which makes these problems hard to solve and prohibitively time consuming. In this paper, we propose a parallel distributed algorithm that uses an adaptive regularizer (PDAR) to solve a joint optimization problem with separable constraints. The regularizer is adaptive and depends on the step size between iterations and the iteration number. We show theoretical convergence of our algorithm to an optimal solution, and use a multi-agent three-bin resource allocation example to illustrate the effectiveness of the proposed algorithm. Numerical simulations show that our algorithm converges to the same optimal solution as other distributed methods, with significantly reduced computational time.

关键词： iterative methods mathematics computing multi-agent systems optimisation parallel algorithms resource allocation

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Trace Bench: An Open Data Set for Trace-Oriented Monitoring

Trace Bench: An Open Data Set for Trace-Oriented Monitoring

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IEEE international conference on Cloud Computing Technology and Science (CloudCom)

作者： Jingwen Zhou Zhenbang Chen Ji Wang Zibin Zheng Michael R. Lyu College of Computer National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China

User request trace-oriented monitoring is an effective method to improve the reliability of cloud systems. However, there are some difficulties in getting traces in practice, which hinder the development of trace-oriented monitoring research. In this paper, we release a fine-grained user request-centric open trace data set, called Trace Bench, collected on a real world cloud storage system deployed in a real environment. During collecting, many aspects are considered to simulate different scenarios, including cluster size, request type, workload speed, etc. Besides recording the traces when the monitored system is running normally, we also collect the traces under the situation with faults injected. With a mature injection tool, 14 faults are introduced, including function faults and performance faults. The traces in Trace Bench are clustered in different files, where each file corresponds to a certain scenario. The whole collection work lasted for more than half a year, resulting in more than 360, 000 traces in 361 files. In addition, we also employ several applications based on Trace Bench, which validate the helpfulness of Trace Bench for the field of trace-oriented monitoring.

关键词： Monitoring Servers Educational institutions Instruments Cloud computing Context Fault diagnosis

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A parallel processing Framework using MapReduce for Content-Based Image Retrieval

A Parallel Processing Framework using MapReduce for Content-...

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11th international conference on ICT and Knowledge Engineering (ICT and KE)

作者： Tungkasthan, Anucha Premchaiswadi, Wichian Siam Univ Grad Sch Informat Technol Bangkok Thailand

ISBN: (纸本)9781479922574

In this paper, a Hadoop MapReduce framework is presented in order to perform distributed processing used for CBIR system. Moreover, Hadoop MapReduce framework is used with the intention of increasing the performance of two main functionalities of data insertion and query processing. Therefore, the main objective of the study is distribution of the image data over a large number of nodes. Some of the techniques used in the paper includes: image indexing and retrieval, parallel processing of indexing, and comparing the similarity of retrieved images

关键词： Image Retrieval CBIR Systems MapReduce Distribuited processing Image processing

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Acceleration of an Asynchronous Message Driven Programming Paradigm on IBM Blue Gene/Q

Acceleration of an Asynchronous Message Driven Programming P...

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IEEE 27th international parallel and distributed processing Symposium (IPDPS)

作者： Kumar, Sameer Sun, Yanhua Kale, Laxmikant V. IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA Univ Illinois Urbana Urbana Urbana IL USA

ISBN: (纸本)9780769549712

IBM Blue Gene/Q is the next generation Blue Gene machine that can scale to tens of Peta Flops with 16 cores and 64 hardware threads per node. However, significant efforts are required to fully exploit its capacity on various applications, spanning multiple programming models. In this paper, we focus on the asynchronous message driven parallel programming model - Charm++. Since its behavior (asynchronous) is substantially different from MPI, that presents a challenge in porting it efficiently to BG/Q. On the other hand, the significant synergy between BG/Q software and Charm++ creates opportunities for effective utilization of BG/Q resources. We describe various novel fine-grained threading techniques in Charm++ to exploit the hardware features of the BG/Q compute chip. These include the use of L2 atomics to implement lockless producer-consumer queues to accelerate communication between threads, fast memory allocators, hardware communication threads that are awakened via low overhead interrupts from the BG/Q wakeup unit. Burst of short messages is processed by using the ManytoMany interface to reduce runtime overhead. We also present techniques to optimize NAMD computation via Quad processing Unit (QPX) vector instructions and the acceleration of message rate via communication threads to optimize the Particle Mesh Ewald (PME) computation. We demonstrate the benefits of our techniques via two benchmarks, 3D Fast Fourier Transform, and the molecular dynamics application NAMD. For the 92,000-atom ApoA1 molecule, we achieved 683 mu s/step with PME every 4 steps and 782 mu s/step with PME every step.

关键词： IBM computers fast Fourier transforms molecular dynamics method multiprocessing systems parallel machines parallel programming

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Look before You Leap: Using the Right Hardware Resources to Accelerate applications

Look before You Leap: Using the Right Hardware Resources to ...

引用

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

作者： Jie Shen Ana Lucia Varbanescu Henk Sips Delft University of Technology The Netherlands University of Amsterdam The Netherlands

GPUs are widely used to accelerate data-parallel applications. However, while the GPU processing capability is enhanced in each generation, the CPU computing power is also increased by adding more cores and widening vector units. Compared to the rapid development of GPUs and CPUs, the bandwidth of the data transfer between GPUs and the host CPU grows much slower, resulting in a data-transfer wall for using GPUs. In this situation, choosing the right mix of hardware resources - i.e., The right hardware configuration - is critically important for improving application performance, and the right choice is a function of the available hardware resources as well as the application and the dataset to be used. In this paper, we present a systematic approach to determine the hardware configuration that leads to the best performance for a given workload. Our approach captures the variation of hardware capabilities and data-transfer overhead for different applications and datasets, and uses modeling and prediction techniques to determine the best-performing hardware configuration. We have tested our approach on 7 applications with 6 datasets per application. The results show that our approach takes the correct decision in 38 out of 42 test cases, achieving up to 12.6×/6.6× performance improvement compared to an uninformed Only-CPU/Only-GPU decision.

关键词： Graphics processing units Hardware Data transfer Mathematical model Throughput Predictive models

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A Scalability Model for distributed Resource Management in Real-Time Online applications

A Scalability Model for Distributed Resource Management in R...

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42nd Annual international conference on parallel processing (ICPP)

作者： Meilaender, Dominik Koettinger, Sebastian Gorlatch, Sergei Univ Munster D-48149 Munster Germany

ISBN: (纸本)9780769551173

We consider a challenging class of highly interactive virtual environments, also known as Real-Time Online Interactive applications (ROIA). Popular examples of ROIA include multi-player online computer games, e-learning and training based on real-time simulations, and other challenging applications. ROIA combine high demands on scalability and real-time user interactivity with the problem of an efficient and economic utilization of resources, which is difficult to achieve due to the changing number of users. This paper proposes a generic scalability model for ROIA that analyzes the application performance during runtime and predicts the demand for load balancing, i.e., when to add/remove resources or redistribute workload. We prove the practical relevance of the model by incorporating it into our RTF-RMS resource management system where it is used to predict the influence of different load-balancing actions on the application scalability. Our model is utilized by RTF-RMS for finding efficient load-balancing actions and thresholds for how often these actions should be applied. We report experimental results on the load balancing of a multi-player online game using predictions from the scalability model.

关键词： Analytical Model Load Balancing Real-Time Framework (RTF) Real-Time Online Interactive applications (ROIA) Scalability

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A Locality-Aware Dynamic Thread Scheduler for GPGPUs 14

A Locality-Aware Dynamic Thread Scheduler for GPGPUs

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14th international conference on parallel and distributed Computing, applications and Technologies (PDCAT)

作者： Huang, Yu-Hao Tseng, Ying-Yu Kuo, Hsien-Kai Yen, Ta-Kan Lai, Bo-Cheng Charles Natl Chiao Tung Univ Dept Elect Engn Hsinchu 30010 Taiwan

ISBN: (纸本)9781479924189

Modern GPGPUs implement on-chip shared cache to better exploit the data reuse of various general purpose applications. Given the massive amount of concurrent threads in a GPGPU, striking the balance between Data Locality and Load Balance has become a critical design concern. To achieve the best performance, the trade-off between these two factors needs to be performed concurrently. This paper proposes a dynamic thread scheduler which co-optimizes both the data locality and load balance on a GPGPU. The proposed approach is evaluated using three applications with various input datasets. The results show that the proposed approach reduces the overall execution cycles by up to 16% when compared with other approaches concerning only one objective.

关键词： Dynamic scheduling Equations Instruction sets Loading Mathematical model Optimization Runtime Data Locality GPU parallel computing locality data instruction sets dynamic scheduling Runtime parallel processing (COMPUTERS) Load balancing Mathematical Model loading THREADS scheduler program GRAPPER PICK UP Graphics processing Unit Program Thread

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