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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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Behavioral Patterns of Various JOIN techniques on Large Databases

Behavioral Patterns of Various JOIN Techniques on Large Data...

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international conference on Circuits, Systems, Communication and Information Technology applications (CSCITA)

作者： Mahajan, Sunita M. Jadhav, Vaishali P. Mumbai Educ Trust Dept Comp Sci Bombay Maharashtra India NMIMS Univ St Francis Inst Technol Res Scholar IT Dept Bombay Maharashtra India

ISBN: (纸本)9781479924943

This paper focused on various challenges occurred during processing of join operation in query optimization. Producing the query result in less execution time, reducing communication cost when data is distributed among different sites, preventing data loss during join operation, eliminating duplicate data during data transfer, reducing the amount of data to be transferred using data compression techniques - are some of the challenges occurred during join operation of the query. Paper suggests four join algorithms such as SEMI-join, BLOOM-join, PERF-join and DERF-join to address these problems. The behavior and performance of these algorithms is checked with four different types of queries such as Star, Clique, Circular and Chain query. Experimental results are carried out with benchmark queries to compare the performance of algorithms on large TPC-H database.

关键词： Query Optimization Semi Join Bloom Join PERF Join DERF Join TPC-H Database

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Communication techniques for Mobile Sensor Networks

Communication Techniques for Mobile Sensor Networks

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28th IEEE international conference on Advanced Information Networking and applications Workshops (IEEE WAINA)

作者： Kanzaki, Akimitsu Nishio, Shojiro Osaka Univ Dept Multimedia Engn Grad Sch Info Sci & Tech Suita Osaka Japan

ISBN: (纸本)9781479926527

In mobile sensor networks (MSNs), since sensor nodes and wireless networks are highly resource constrained, and it is highly required to manage sensor data in flexible and efficient manners. Under the MEXT research project(1) entitled "Studies on Efficient Data processing techniques for Mobile Sensor Networks," we have conducted researches on data management in MSNs. In this paper, we report some of our achievements in a sub-area of this project, which mainly addresses communication protocols for efficient data gathering in MSNs. In particular, we first show our achievements on how to efficiently gather sensor data using mobile sensor nodes in each of sparse and dense environments. We also show our another achievement on how to transmit sensor data assuming an environment where multiple mobile sinks exist.

关键词： mobile sensor networks communication protocols data gathering mobile sink

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A Framework for Tracking Memory Accesses in Scientific applications 43

A Framework for Tracking Memory Accesses in Scientific Appli...

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43rd international conference on parallel processing Workshops, ICPPW 2014

作者： Peña, Antonio J. Balaji, Pavan Mathematics and Computer Science Division Argonne National Laboratory ArgonneIL60439 United States

ISBN: (纸本)9781479956159

Profiling is of great assistance in understanding and optimizing applications' behavior. Today's profiling techniques help developers focus on the pieces of code leading to the highest penalties according to a given performance metric. In this paper we describe a pair of tools we have extended to complement the traditional algorithm-oriented analysis. Our extended tools provide new object-differentiated profiling capabilities that help software developers and hardware designers (1) understand access patterns, (2) identify unexpected access patterns, and (3) determine whether a particular memory object is consistently featuring a troublesome access pattern. Memory objects found in this way may have gone unnoticed with the traditional profiling approach. This additional view may lead developers to think of different ways of storing data, leveraging different algorithms, or employing different memory subsystems in future heterogeneous memory systems. © 2014 IEEE.

关键词： Heterogeneous memory Profiling Valgrind

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Automatic Generation of Optimized Workflow for distributed Computations on Large-Scale Matrices 12

Automatic Generation of Optimized Workflow for Distributed C...

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12th international conference on Service-Oriented Computing (ICSOC)

作者： Sabry, Farida Erradi, Abdelkarim Nassar, Mohamed Malluhi, Qutaibah M. Qatar Univ KINDI Ctr Comp Res Doha Qatar

ISBN: (纸本)9783662453919;9783662453902

Efficient evaluation of distributed computation on arge-scale data is prominent in modern scientific computation;especially analysis of big data, image processing and data mining applications. This problem is particularly challenging in distributed environments such as campus clusters, grids or clouds on which the basic computation routines are offered as web/cloud services. In this paper, we propose a locality-aware workflow-based solution for evaluation of large-scale matrix expressions in a distributed environment. Our solution is based on automatic generation of BPEL workflows in order to coordinate long running, asynchronous and parallel invocation of services. We optimize the input expression in order to maximize parallel execution of independent operations while reducing the matrix transfer cost to a minimum. Our approach frees the end-user of the system from the burden of writing and debugging lengthy BPEL workflows. We evaluated our solution on realistic mathematical expressions executed on large-scale matrices distributed on multiple clouds.

关键词： location-aware optimization distributed computations BPEL workflows large-scale matrices

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distributed keyword search over RDF via MapReduce

Distributed keyword search over RDF via MapReduce

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11th international conference on Semantic Web: Trends and Challenges, ESWC 2014

作者： De Virgilio, Roberto Maccioni, Antonio Dipartimento di Ingegneria Universitá Roma Tre Rome Italy

ISBN: (纸本)9783319074429

Non expert users need support to access linked data available on the Web. To this aim, keyword-based search is considered an essential feature of database systems. The distributed nature of the Semantic Web demands query processing techniques to evolve towards a scenario where data is scattered on distributed data stores. Existing approaches to keyword search cannot guarantee scalability in a distributed environment, because, at runtime, they are unaware of the location of the relevant data to the query and thus, they cannot optimize join tasks. In this paper, we illustrate a novel distributed approach to keyword search over RDF data that exploits the MapReduce paradigm by switching the problem from graph-parallel to data-parallel processing. Moreover, our framework is able to consider ranking during the building phase to return directly the best (top-k) answers in the first (k) generated results, reducing greatly the overall computational load and complexity. Finally, a comprehensive evaluation demonstrates that our approach exhibits very good efficiency guaranteeing high level of accuracy, especially with respect to state-of-the-art competitors. © 2014 Springer international Publishing.

关键词： MapReduce

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Image registration techniques using parallel computing in multicore environment and its applications in medical imaging: An overview 5

Image registration techniques using parallel computing in mu...

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5th IEEE international conference on Computer and Communication Technology, ICCCT 2014

作者： Saxena, Sanjay Sharma, Shiru Sharma, Neeraj Varanasi UP India

ISBN: (纸本)9781479967575

Image Registration is the key step of Image processing as it is the process to locate most accurate relative orientation among two or more images, captured at the same or different times by distinguishable or indistinguishable sensors to increase the information content. For speed optimization of Image Registration, There have been developed numerous approaches till now based on CPU platforms, GPU, CUDA Programming Models etc. Purpose of this paper is to provide a comprehensive review of the existing literature available on Image registration methods based on parallel computing in Multi core architecture. Another considerable intention of this paper is to describe the various applications of image registration using parallel computing in Medical imaging as it can be applied for different modalities of medical images. © 2014 IEEE.

关键词： Image registration

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Simulation speedup of ns-3 using checkpoint and restore 14

Simulation speedup of ns-3 using checkpoint and restore

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2014 Workshop on ns-3, WNS3 2014

作者： Harrigan, Kyle Riley, George Georgia Tech Research Institute Atlanta GA United States Department of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA United States

ISBN: (纸本)9781450330039

Given that large-scale network simulations are a significant part of active research [6], and that such simulations are known to be computationally and resource intensive, it is still of interest to find innovative ways to achieve faster execution times and to more efficiently provide data and results for the researcher. While utilization of parallel programming techniques and frameworks such as MPI, CUDA, and OpenCL are valid approaches and very useful in speeding up computations, few of these techniques seek to reduce repetitive, uninteresting, or non-changing segments of simulation runs which are unnecessarily repeated, for instance during initialization, and which are not of interest to the end result being studied. Recent advances in process checkpointing utilities, such as distributed Multithreaded Checkpointing (DMTCP) [1], which support practical user-space checkpointing of a wide variety of distributed, multithreaded applications and support the use of important libraries such as MPI, enable innovative techniques for achieving computational savings and provide the potential for a more generic mechanism of moving simulations forward and backward in time efficiently We present an approach and prototype module for ns-3 which provides an API for checkpointing running ns-3 applications at arbitrary times, restoring these applications to a running state, and for modifying parameters of the restored simulation before process continuation.

关键词： parallel programming

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Efficient parallel Implementation of Morphological Operation on GPU and FPGA

Efficient Parallel Implementation of Morphological Operation...

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IEEE international conference on Security, Pattern Analysis, and Cybernetics (SPAC)

作者： Li, Teng Dou, Yong Jiang, Jingfei Gao, Jing Natl Univ Def & Technol Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China AIR CHINA LTD Informat Management Dept Beijing Peoples R China

ISBN: (纸本)9781479953530

Morphological operation constitutes one of a powerful and versatile image and video applications applied to a wide range of domains, from object recognition, to feature extraction and to moving objects detection in computer vision where real-time and high-performance are required. However, the throughput of morphological operation is constrained by the convolutional characteristic. In this paper, we analysis the parallelism of morphological operation and parallel implementations on the graphics processing unit (GPU), and field programming gate array (FPGA) are presented. For GPU platform, we propose the optimized schemes based on global memory, texture memory and shared memory, achieving the throughput of 942.63 Mbps with 3x3 structuring element. For FPGA platform, we present an optimized method based on the traditional delay-line architecture. For 3x3 structuring element, it achieves a throughput of 462.64 Mbps.

关键词： Morphological operation Computer vision GPU FPGA

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international Workshops on parallel processing, Euro-Par 2014

International Workshops on Parallel Processing, Euro-Par 201...

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The proceedings contain 48 papers. The special focus in this conference is on parallel processing. The topics include: On parallelization of the openFOAM-based solver for the heat transfer in electrical power cables;CPU and GPU performance of large scale numerical simulations in geophysics;parallelizing a CAD model processing tool from the automotive industry;parallelization of a tridimensional finite element program for structural behaviour analysis;data parallelism in traffic control tables with arrival information;parallel shared-memory multi-objective stochastic search for competitive facility location;automata-based dynamic data processing for clouds;fast parallel connected components algorithms on GPUs;concurrent data structures in architectures with limited shared memory support;non-linear iterative optimization method for locating particles using HPC techniques;interactive tuning of biological analysis pipelines using iterative processing;the role of trusted relationships on content spread in distributed online social networks;hierarchical approach for green workload management in distributed data centers;the impact of routing attacks on pastry-based P2P online social networks;SLA-based cloud security monitoring;a survey on parallel and distributed multi-agent systems;resolving conflicts between multiple competing agents in parallel simulations;programmability and performance of parallel ECS-based simulation of multi-agent exploration models;exploiting D-mason on parallel platforms;reproducible experiments in parallel computing;a study of current practices in parallel computing and an automated performance-aware approach to reliability transformations.

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An Efficient Memory Model for Implementing Image Resizing Algorithms in a distributed Environment 16

An Efficient Memory Model for Implementing Image Resizing Al...

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16th UKSim-AMSS international conference on Computer Modelling and Simulation (UKSim)

作者： Ali, Syed Hayat, Liaqat Ajman Univ Sci & Technol Coll Informat Technol Ajman U Arab Emirates Yanbu Ind Coll Elect & Instrumentat Engn Technol Yanbu Saudi Arabia

ISBN: (纸本)9781479949236

Image resizing algorithms are a classic case of algorithms involving local operations over a region of pixels in an image. The objective is to produce a reduced or enlarged image while maintaining original information content or minimizing the mean square error between corresponding pixels of original and resized images. Most resizing algorithms rely on pixel values within a pre-defined neighborhood of a pixel in the original image to compute pixel values in target images. High frequency or high energy pixel regions in an image are more prone to distortions/errors in the resized image. Content-aware algorithms minimize this impact at the cost of more computational complexity and cost. parallel/distributed implementations of such algorithms require an efficient methodology of image data partitioning to minimize interdependency of the processing units and/or memory storage to avoid shared memory access bottleneck. A restricted shared memory model is described herein that is well-tailored for most of the computational techniques used in image resizing algorithms. Implementation results are described for some well-known algorithms that demonstrate the suitability of the model and its scalability to cater for large image sizes.

关键词： Image resizing distributed processing restricted shared memory model

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