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检索条件"主题词=Parallel and distributed computing"

共 272 条记录，以下是181-190 订阅

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A vector model for routing queries in web search engines

A vector model for routing queries in web search engines

引用

International Conference on Computational Science (ICCS)

作者： Oyarzun, Mauricio S. Gonzalez, Senen Mendoza, Marcelo Ferrarotti, Flavio Chacon, Max Marin, Mauricio Univ Santiago Chile Santiago Chile Univ Chile Santiago Chile Res Latin Amer Santiago Chile

This paper proposes a method for reducing the number of search nodes involved in the solution of queries arriving to a Web search engine. The method is applied by the query receptionist machine during situations of sudden peaks in query traffic to reduce the load on the search nodes. The experimental evaluation based on actual traces from users of a major search engine, shows that the proposed method outperforms alternative strategies. This is more evident for systems composed of a large number of search nodes which indicates that the method is also more scalable than the alternative strategies. (C) 2010 Published by Elsevier Ltd.

关键词： parallel and distributed computing Information Retrieval Web Search Engines

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Towards distributed Software Resilience in Asynchronous Many-Task Programming Models 10

Towards Distributed Software Resilience in Asynchronous Many...

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IEEE/ACM 10th Workshop on Fault Tolerance for HPC at eXtreme Scale (FTXS)

作者： Gupta, Nikunj Mayo, Jackson R. Lemoine, Adrian S. Kaiser, Hartmut Indian Inst Technol Dept CSE Roorkee Uttar Pradesh India Sandia Natl Labs Livermore CA USA Louisiana State Univ Ctr Computat Technol Baton Rouge LA 70803 USA AMD Inc Austin TX USA STE AR Grp Noida India

ISBN: (纸本)9780738110806

Exceptions and errors occurring within mission critical applications due to hardware failures have a high cost. With the emerging Next Generation Platforms (NGPs), the rate of hardware failures will likely increase. Therefore, designing our applications to be resilient is a critical concern in order to retain the reliability of results while meeting the constraints on power budgets. In this paper, we discuss software resilience in AMTs at both local and distributed scale. We choose HPX to prototype our resiliency designs. We implement two resiliency APIs that we expose to the application developers, namely task replication and task replay. Task replication repeats a task n-times and executes them asynchronously. Task replay reschedules a task up to n-times until a valid output is returned. Furthermore, we expose algorithm based fault tolerance (ABFT) using user provided predicates (e.g., checksums) to validate the returned results. We benchmark the resiliency scheme for both synthetic and real world applications at local and distributed scale and show that most of the added execution time arises from the replay, replication or data movement of the tasks and not the boilerplate code added to achieve resilience.

关键词： software resilience parallel and distributed computing asynchronous many-task systems HPX

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Comparative Evaluation of Dependability for Voltage and Reactive Power Control by Modified Brain Storm Optimization using Individual and Sub-population based parallel Multi-Population

Comparative Evaluation of Dependability for Voltage and Reac...

引用

IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Matsumoto, Kaichi Fukuyama, Yoshikazu Meiji Univ Grad Sch Adv Math Sci Tolyo Japan

ISBN: (纸本)9781728125473

Voltage and reactive power control (VRPC) is one of Mixed Integer Nonlinear Programming (MINLP) problems. Evolutionary computation (EC) based VRPC methods have been developed for solving VRPC problems. Since VRPC is an online control, it is necessary to solve a VRPC problem in a limited VRPC interval. Recently, high level of renewable energy penetration and progress of deregulation in power systems require to shorten the VRPC interval and to solve a large-scale VRPC problem in the VRPC interval. Namely, Fast calculation is required in VRPC. Application of parallel and distributed computing (PDC) is a practical option for solving this challenge. However, since power system is a social infrastructure, a dependable method is required for keeping quality of solutions even if several servers cannot return the calculation results due to various faults. When PDC is applied to an EC method using multi-population (MP), there are two ways for realization of parallel computation, namely sub-population based parallel multi-population (PMP) and individual based PMP. No papers have ever compared the two methods from a dependability point of view. This paper presents comparative evaluation of dependability for VRPC by modified brain storm optimization (MBSO) using the individual and the sub-population based PMP. Simulation results with an IEEE 118 bus bench mark system indicate higher dependability of the method using the individual based PMP than the method using sub-population based PMP.

关键词： voltage and reactive power control individual based multi-population parallel and distributed computing dependability modified brain storm optimization evolutionary computation

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parallel Particle Swarm Optimization for Reactive Power and Voltage Control Verifying Dependability

Parallel Particle Swarm Optimization for Reactive Power and ...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Fukuyama, Yoshikazu Meiji Univ Dept Network Design Sch Interdisciplinary Math Sci Tokyo Japan

ISBN: (纸本)9781479974924

This paper presents a parallel particle swarm optimization (PSO) for reactive power and voltage control (Volt/Var Control: VVC) in electric power systems verifying dependability of the control. Considering high penetration of renewable energies and deregulation of power systems, electric power flows can change suddenly and operators in control centers have to control voltage in wider power systems. Therefore, VVC is required to shorten the control interval and handle larger-scale power systems. One of the solutions for this problem is applications of parallel and distributed computing. Since electric power systems is one of the infrastructures of social community, sustainable voltage control is crucial and dependability is strongly required for VVC. This paper investigates not only fast computation by parallel computation but also dependability of parallel PSO for VVC. The results are meaningful for practical parallel computation by PSO in actual VVC operations.

关键词： parallel and distributed computing particle swarm optimization dependability reactive power and voltage control

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parallel and distributed Sparse Optimization

Parallel and Distributed Sparse Optimization

引用

47th Asilomar Conference on Signals, Systems, and Computers

作者： Peng, Zhimin Yan, Ming Yin, Wotao Univ Calif Los Angeles Dept Math Los Angeles CA 90024 USA

ISBN: (纸本)9781479923908

This paper proposes parallel and distributed algorithms for solving very large-scale sparse optimization problems on computer clusters and clouds. Modern datasets usually have a large number of features or training samples, and they are usually stored in a distributed manner. Motivated by the need of solving sparse optimization problems with large datasets, we propose two approaches including (i) distributed implementations of prox-linear algorithms and (ii) GRock, a parallel greedy block coordinate descent method. Different separability properties of the objective terms in the problem enable different data distributed schemes along with their corresponding algorithm implementations. We also establish the convergence of GRock and explain why it often performs exceptionally well for sparse optimization. Numerical results on a computer cluster and Amazon EC2 demonstrate the efficiency and elasticity of our algorithms.

关键词： sparse optimization l(1) minimization LASSO parallel and distributed computing GRock

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String Sorting on Multi and Many-threaded Architectures: A Comparative Study

String Sorting on Multi and Many-threaded Architectures: A C...

引用

International Conference on High Performance computing and Applications (ICHPCA)

作者： Neelima, B. Narayan, Aniian S. Prabhu, Rithesh G. NMAM Inst Technol Dept Comp Sci & Engn Udupi India

ISBN: (纸本)9781479959587

The increase in the amount of data is evident in recent times. The amount of data stored and retrieved is increasing at a fast rate. Processing text data consumes large amount of memory in terms of storage and extraction. Sorting the stored data is one of the most favorable methods that can be used in order to increase the efficiency of extracting stored data. Graphic Processing Units (GPUs) have evolved from being used as dedicated graphic rendering modules to being used to exploit fast parallelism for large computational purposes. The use of GPUs for sorting strings large in size has produced effective and fast results when compared to using CPUs. This paper produces a comparative study on the most popular and efficient string sorting algorithms that have been implemented on CPU and GPU machines. This paper also proposes an efficient parallel multi-key quicksort implementation which uses ternary search tree in order to increase the speed up and efficiency of sorting large set of string data.

关键词： Hybrid machines Graphic processing units String sorting parallel and distributed computing parallel string sorting

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High Performance computing for Eigenvalue Solver in Density-Matrix Renormalization Group Method: parallelization of the Hamiltonian Matrix-Vector Multiplication

High Performance Computing for Eigenvalue Solver in Density-...

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8th International Conference on High Performance computing for Computational Science (VECPAR 2008)

作者： Yamada, Susumu Okumura, Masahiko Machida, Masahiko Japan Atom Energy Agcy CCSE Taito Ku 6-9-3 Higashi Ueno Tokyo 1100015 Japan JST CREST Kawaguchi Saitama 3300012 Japan

ISBN: (纸本)9783540928584

The Density Matrix Renormalization Group (DMRG) method is widely used by computational physicists as a high accuracy tool to obtain the ground state of large quantum lattice models. Since the DMRG method has been originally developed for 1-D models, many extended method to a 2-D model have been proposed. However, some of them have issues in term of their accuracy. It is expected that the accuracy of the DMRG method extended directly to 2-D models is excellent. The direct extension DMRG method demands an enormous memory space. Therefore, we parallelize the matrix-vector multiplication irk iterative methods for solving the eigenvalue problem, which is the most time-and memory-consuming operation. We find that the parallel efficiency of the direct extension DMRG method shows a good one as the number of states kept increases.

关键词： parallel and distributed computing DMRG method matrix-vector multiplication eigenvalue problem quantum lattice systems

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distributed computing in accelerator physics theory and technology

Distributed computing in accelerator physics theory and tech...

引用

International Conference on Computational Science (ICCS)

作者： Andrianov, S. St Petersburg State Univ Fac Appl Math & Control Proc St Petersburg 198504 Russia

This report is devoted to discussion of numerical and symbolic computing ratio in beam physics. We tray to draw attention on basic conceptual and computational problems first of all. It is known that the main problem in modern computational beam physics connected with high performance computing realization. The most of used approaches are not appropriate for computing using multiprocessing systems. Here we give some possible solutions, which based on a matrix presentation of necessary information and modern information technologies. (C) 2010 Published by Elsevier Ltd.

关键词： Beam physics Lie algebraic tools symbolic parallel and distributed computing

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Implementation and Performance of FPGA-Accelerated Particle Flow Filter

Implementation and Performance of FPGA-Accelerated Particle ...

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Conference on Signal and Data Processing of Small Targets

作者： Charalampidis, Dimitrios Jilkov, Vesselin P. Wu, Jiande Univ New Orleans Dept Elect Engn New Orleans LA 70148 USA

ISBN: (纸本)9781628417623

The particle flow filters, proposed by Daum & Hwang, provide a powerful means for density-based nonlinear filtering but their computation is intense and may be prohibitive for real-time applications. This paper proposes a design for superfast implementation of the exact particle flow filter using a field-programmable gate array (FPGA) as a parallel environment to speedup computation. Simulation results from a nonlinear filtering example are presented to demonstrate that using FPGA can dramatically accelerate particle flow filters through parallelization at the expense of a tolerable loss in accuracy as compared to nonparallel implementation.

关键词： Nonlinear filtering particle flow filter parallel and distributed computing FPGA

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String Matching on a multicore GPU using CUDA

String Matching on a multicore GPU using CUDA

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13th Panhellenic Conference on Informatics (PCI 2009)

作者： Kouzinopoulos, Charalampos S. Margaritis, Konstantinos G. Univ Macedonia Dept Appl Informat Parallel & Distributed Proc Lab Thessaloniki 54006 Greece

ISBN: (纸本)9780769537887

Graphics Processing Units (GPUs) have evolved over the past few years from dedicated graphics rendering devices to powerful parallel processors, outperforming traditional Central Processing Units (CPUs) in many areas of scientific computing. The use of GPUs as processing elements was very limited until recently, when the concept of General-Purpose computing on Graphics Processing Units (GPGPU) was introduced. GPGPU made possible to exploit the processing power and the memory bandwidth of the GPUs with the use of APIs that hide the GPU hardware from programmers. This paper presents experimental results on the parallel processing for some well known on-line string matching algorithms using one such GPU abstraction API, the Compute Unified Device Architecture (CUDA).

关键词： string matching algorithms CUDA GPGPU parallel and distributed computing stream processing

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