Message Passing ( MP) and distributed Shared Memory (DSM) are the two most common approaches to distributed parallel computing. MP is difficult to use, whereas DSM is not scalable. Performance scalability and ease of ...
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Message Passing ( MP) and distributed Shared Memory (DSM) are the two most common approaches to distributed parallel computing. MP is difficult to use, whereas DSM is not scalable. Performance scalability and ease of programming can be achieved at the same time by using navigational programming (NavP). This approach combines the advantages of MP and DSM, and it balances convenience and flexibility. Similar to MP, NavP suggests to its programmers the principle of pivot-computes and hence is efficient and scalable. Like DSM, NavP supports incremental parallelization and shared variable programming and is therefore easy to use. The implementation and performance analysis of real-world algorithms, namely parallel Jacobi iteration and parallel Cholesky factorization, presented in this paper supports the claim that the NavP approach is better suited for general-purpose paralleldistributed programming than either MP or DSM.
The modeling and solving a transcendental eigenvalue problem are important issues in the transfer matrix method for linear multibody systems. Based on the recursive eigenvalue search algorithm for transfer matrix meth...
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The modeling and solving a transcendental eigenvalue problem are important issues in the transfer matrix method for linear multibody systems. Based on the recursive eigenvalue search algorithm for transfer matrix method for linear multibody system, the distributedparallel approach for assembling overall transfer matrix and searching eigenvalues is proposed. This is achieved based on Message parallel Interface. The influence of the CPU core number as well as the distributed network environment on the final computational time is analyzed through numerical examples of both a non-uniform beam and a multiple launch rocket system. The results indicate that the computational time is significantly reduced by the proposed parallelcomputing method, so that the computational efficiency on optimization and design of complex multibody systems can be improved.
Three-dimensional (3D) images have become increasingly popular in practice. They are commonly used in medical imaging applications. In such applications, it is often critical to compare two 3D images, or monitor a seq...
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Three-dimensional (3D) images have become increasingly popular in practice. They are commonly used in medical imaging applications. In such applications, it is often critical to compare two 3D images, or monitor a sequence of 3D images. To make the image comparison or image monitoring valid, the related 3D images should be geometrically aligned first, which is called image registration (IR). However, IR for 3D images would take much computing time, especially when a flexible method is considered, which does not impose any parametric form on the underlying geometric transformation. Here, the authors explore a fast-computing environment for 3D IR based on the distributed parallel computing. The selected 3D IR method is based on the Taylor's expansion and 3D local kernel smoothing. It is flexible, but involves much computation. The authors demonstrate that this fast-computing environment can effectively handle the computing problem while keeping the good properties of the 3D IR method. The method discussed here is therefore useful for applications involving big data.
Fine flow and heat transfer characteristics are critical to nuclear reactor safety. However, a comprehensive CFD calculation of the entire reactor core requires substantial computing resources, restricting the researc...
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Fine flow and heat transfer characteristics are critical to nuclear reactor safety. However, a comprehensive CFD calculation of the entire reactor core requires substantial computing resources, restricting the research domain's scope. To address this issue, we propose a distributedparallel (DP) computing scheme, tailored specifically for reactor cores using plate-type fuel assemblies. This study focuses on the thermal-hydraulic calculation of the large domain of a reactor core utilizing plate-type fuel assembly, based on the Computational Fluid Dynamics (CFD) method. This innovative solution enables the completion of extensive domain CFD calculations using modestly equipped personal workstations (8 cores, 128G RAM), which traditionally would require supercomputing platforms. To verify the distributed-parallelcomputing technique, it is successfully applied to all standard, full-length fuel assemblies in the China Advanced Research Reactor (CARR). In the result analysis, it was observed that detailed results could be obtained with reduced computational resources, demonstrating a significant breakthrough for CFD engineering analysis.
With the continuous improvement in the efficiency of the heavy-haul railway freight transportation, the pressure on on-site maintenance is increasing. In-depth research on fault characteristics carries significant imp...
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With the continuous improvement in the efficiency of the heavy-haul railway freight transportation, the pressure on on-site maintenance is increasing. In-depth research on fault characteristics carries significant importance for fault scientific judgment and fault prevention. This study proposes an efficient association rule mining (ARM) algorithm, HM-RDHP, for analyzing fault data from heavy-haul railway freight trains. The algorithm introduces distributed parallel computing technology, integrating the MapReduce framework and HBase on the Hadoop platform to process large volumes of complex fault data efficiently. Experimental results show that the HM-RDHP algorithm can efficiently uncover hidden patterns and associations within the fault data of heavy-haul railway freight trains. The mined association rules provide a valuable reference model to aid in predictive maintenance and fault prevention strategies for freight train maintenance departments.
The analysis of modem power system becomes more computation intensive, and has to be performed in a dispersed IT infrastructure due to the inherently distributed topology of power system. Grid computing is potentially...
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ISBN:
(纸本)0769525547
The analysis of modem power system becomes more computation intensive, and has to be performed in a dispersed IT infrastructure due to the inherently distributed topology of power system. Grid computing is potentially an ideal solution for electric power system and power network infrastructure, also provides potential application field for grid computing because grid computing is most efficient in a large organization. This paper presents a new version of MPI (Message Passing Interface) based on P2P, WD-MPI, in order to exploit the maximum performance in a heterogeneous environment for power system distributedcomputing. The problems of traditional MPI and some versions of modified MPI to improve its performance on heterogeneous and wide area network are analyzed. The system structure is presented and the design of the system, including asynchronous iterative algorithm, task and resource partition, is presented. The power flow calculation problem of an IEEE 300 bus system is used to compare the performances of the proposed scheme and previous solutions. The test is performed in a grid environment built in campus, which can simulate the behavior of wide area network to some extent. The test results show that the P2P based WD-MPI can give better performance than that of MPICH, MPICH-G2 and Globus solution.
A task level intelligent computing architecture, called as smart workstation cluster distributed parallel computing model, is presented for transient stability constrained total transfer capability (TTC) evaluation of...
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ISBN:
(纸本)9781424442409
A task level intelligent computing architecture, called as smart workstation cluster distributed parallel computing model, is presented for transient stability constrained total transfer capability (TTC) evaluation of large scale interconnected power system with respect to a specified contingency set. The proposed intelligent distributed parallel computing mode can effectively integrate the heterogeneous distributedcomputing resources around internet and implement the dynamic load balancing so as to make full use of the whole system computing performance. Furthermore, the dynamic scalability and fault-tolerance of the proposed computing architecture are analyzed and developed as well. The case studies have been carried out on a real-sized Chinese power system, and results demonstrate the practicability and effectiveness of the proposed model.
This paper presents a mobile-agent-based distributed parallel computing middleware (MDPCM) that is used to implement distributed parallel computing by sharing computing resources among Internet users. The middleware i...
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ISBN:
(纸本)9789806560550
This paper presents a mobile-agent-based distributed parallel computing middleware (MDPCM) that is used to implement distributed parallel computing by sharing computing resources among Internet users. The middleware is divided into two layers with characteristics of the mobile agent technology and it provided basic services for the distributed parallel computing, especially system communication, job migration and fault tolerance mechanism. The main implementation technologies are analyzed and discussed. A prototype system MDPCM-based is implemented and the experiment results are shown.
Higher-order tensor renormalization group (HOTRG) is a coarse-graining algorithm for approximating the partition function in the field of elementary particle physics using a tensor network. Coarse-graining in HOTRG co...
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ISBN:
(纸本)9781538655559
Higher-order tensor renormalization group (HOTRG) is a coarse-graining algorithm for approximating the partition function in the field of elementary particle physics using a tensor network. Coarse-graining in HOTRG comprises an approximation step and a contraction step, and the contraction step is performed with tensor reorderings and matrix products. In this paper, we introduce a naive parallel implementation of HOTRG and propose optimal reordering procedures for a three-dimensional (3D) classical cubic lattice Ising model. Numerical experiments on the K computer show that the elapsed time of the proposed procedure is 6.88 times faster than the naive one for the reorderings.
Grid computing provides new solutions for numerous complex problems. It is an inevitable trend to implement the distributed parallel computing of large-scale problems with the grid. This paper presents two implementat...
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ISBN:
(纸本)0769525814
Grid computing provides new solutions for numerous complex problems. It is an inevitable trend to implement the distributed parallel computing of large-scale problems with the grid. This paper presents two implementations for distributed parallel computing on Globus Toolkit, a wide-used grid environment. The first implementation, Loosely Coupled parallel Services is used to achieve the large-scale parallelcomputing that can be broken down into independent sub-jobs by using the corresponding implementation framework, and the second implementation, Grid MPI parallel Program is able to deal with specialized applications, which can't easily be split up into numerous independent chunks, by using the proposed implementation framework. Finally, Two examples of large-scale parallelcomputing based on proposed implementations are achieved and the experimental results are shown. We make a beneficial attempt to implement distributed parallel computing on grid computing environments.
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