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MATLAB^A®: A Language for parallel computing

INTERNATIONAL JOURNAL OF parallel PROGRAMMING 2009年第1期37卷 3-36页

作者： Sharma, Gaurav Martin, Jos The MathWorks Natick MA 01760 USA MathWorks Ltd Cambridge CB4 0HH England

parallel computing with the MATLAB(A (R)) language and environment has received interest from various quarters. The parallel computing toolbox(TM) and MATLAB(A (R)) Distributed computing Server(TM) from The MathWorks are among several available tools that offer this capability. We explore some of the key features of the parallel MATLAB language that these tools offer. We describe the underlying mechanics as well as the salient design decisions and rationale for certain features in the toolset. The paper concludes by identifying some issues that we must address as the language features evolve.

关键词： parallel MATLAB parallel language design parallel computing toolbox

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A parallel computing approach for integrated security assessment of power system

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年 78卷 591-599页

作者： Varshney, Sarika Srivastava, Laxmi Pandit, Manjaree Madhav Inst Sci & Technol Gwalior MP India

Fast and accurate assessment of integrated security of present day complex and highly interconnected power system within time frame is a challenging task. The traditional methods used for integrated security assessment are fast but approximate. On the other hand, full simulation methods provide more accurate security assessment, but require large computation time. This paper proposes the use of parallel computing for fast and accurate assessment of integrated security of power system by running full Newton Raphson (NR) load flow program with sparsity technique to compute real power flow or MW performance index (MWPI), and voltage performance index (VPI), and continuation power flow program with sparsity technique to compute voltage stability index (VSI) for all possible single line outage contingencies. The proposed work has been carried out using the Matlab parallel computing toolbox Software (PCTS). To implement parallel computing, the job scheduler, a part of POTS, divides a computationally intensive job into various tasks and distributes these tasks to its assigned workers for evaluation. Effectiveness of the proposed approach has been demonstrated on IEEE 30-bus system and a practical NREB 246-bus Indian power system. As the proposed method utilizes NR load flow and continuation load flow programs, the accurate post contingency operating status of a power system is also available, which can be used for appropriate corrective actions planning to bring the power system back into secure state. The proposed approach is quite accurate and fast and hence can be implemented for integrated security assessment of practical power systems in smart grid environment also. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： parallel computing toolbox Speed up Integrated security assessment MW performance index Voltage performance index Voltage stability index

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parallel PROGRAMMING IN MATLAB

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE computing APPLICATIONS 2009年第3期23卷 277-283页

作者： Luszczek, Piotr Univ Tennessee Knoxville TN 37996 USA

A visit to the neighborhood PC retail store provides ample proof that we are in the multi-core era. The key differentiator among manufacturers today is the number of cores that they pack onto a single chip. The clock frequency of commodity processors has reached its limit, however, and is likely to stay below 4 GHz for years to come. As a result, adding cores is not synonymous with increasing computational power. To take full advantage of the performance enhancements offered by the new multi-core hardware, a corresponding shift must take place in the software infrastructure - a shift to parallel computing.

关键词： MATLAB parallel computing toolbox multi-core parallel computing parallel programming

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parallel Implementation of Energy-Based Target Localization Methods in Wireless Sensor Networks

Parallel Implementation of Energy-Based Target Localization ...

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IEEE SOUTHEASTCON

作者： Luo, Zhenxing Min, Paul S. Washington Univ Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781479965854

This paper discusses the parallel implementation of an energy-based target localization method. This energy-based target localization method is presented first. Then, techniques used in its parallel implementation are discussed. Finally, this method is implemented using different numbers of cores. Other energy-based target localization methods can be implemented similarly. Simulation results showed that the parallel implementation could significantly reduce the computation time. However, the computation time required when two cores were used was more than half of that when a single core was used.

关键词： MATLAB parallel computing toolbox parallel Implementation Target Localization

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Simulation of a Model for Refactoring Approach for parallelism Using parallel computing Tool Box 1st

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1st International Conference on Information and Communication Technology for Intelligent Systems (ICTIS)

作者： Makka, Shanthi Sagar, B. B. BITs Mesra Noida CampusSect 15 Noida India JRE Grp Inst Plot 5678 Greater Noida 201308 Uttar Pradesh India

ISBN: (纸本)9783319309279;9783319309262

Refactoring is the process of retaining the behavior of a program by making changes to the structure of a program. Initially refactoring is used only for sequential programs, but due to highly configurated architectural availability, it also aids parallel programmers in implementing their parallel applications. Refactoring provides many advantages to parallel programmers, in identifying independent modules, in refining process of programs, it also helps in separating concerns between application and system programmers, and it reduces the time for deployment. All mentioned advantages benefit the programmer in writing parallel programs. The approach for refactoring using multi core system is already developed. Hence all these advantages made us to thought of a system to develop refactoring approach for parallelism which uses heterogeneous parallel architectures which uses combination of both Graphic Processing Unit (GPU) and Central Processing Unit (CPU). A Tool in MATLAB, parallel computing toolbox can be used to execute programs on multiple processing elements simultaneously with local workers available in the toolbox, which takes benefit of GPUs. This tool box uses complete processing speed of multi core system to execute applications on local workers without changing the code. Our suggested model can be simulated by using parallel computing toolbox.

关键词： Refactoring MATLAB parallel computing toolbox GPU CPU Heterogeneous parallel architecture

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Remarks on parallel computations in MATLAB environment

Remarks on parallel computations in MATLAB environment

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Conference on Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments

作者： Opalska, Katarzyna Opalski, Leszek Warsaw Univ Technol Inst Elect Syst PL-00665 Warsaw Poland

ISBN: (纸本)9780819497857

The paper attempts to summarize author's investigation of parallel computation capability of MATLAB environment in solving large ordinary differential equations (ODEs). Two MATLAB versions were tested and two parallelization techniques: one used multiple processors-cores, the other - CUDA compatible Graphics Processing Units (GPUs). A set of parameterized test problems was specially designed to expose different capabilities/limitations of the different variants of the parallel computation environment tested. Presented results illustrate clearly the superiority of the newer MATLAB version and, elapsed time advantage of GPU-parallelized computations for large dimensionality problems over the multiple processor-cores (with speed-up factor strongly dependent on the problem structure).

关键词： MATLAB parallel computing toolbox efficient simulation Ordinary Differential Equations (ODE) computation parallelization GPU multithreading Iterated Runge Kutta (IRK) integration method

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Application of parallel computing In Robust Optimization Design Using MATLAB 5

Application of Parallel Computing In Robust Optimization Des...

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Fifth International Conference on Instrumentation & Measurement, Computer, Communication, and Control (IMCCC)

作者： Wang, Huijing Lu, Zhigang Zhao, Hao Feng, Huibo Yanshan Univ Key Lab Power Elect Energy Conservat & Motor Dr H Qinhuangdao 066004 Peoples R China State Grid Hebei Elect Power Co Shijiazhuang 050021 Peoples R China

ISBN: (纸本)9781467377232

This article provides an effective way to alleviate the long running defect of multi-objective intelligent optimization algorithms and enhance its ability to solve the robust optimization (RO) design. It describes the implementation of parallel computing for intelligent optimization algorithms based on the MATLAB parallel computing toolbox (PCT) and Distributed computing Server (DCS). In order to test the effectiveness of the proposed method, the parallel multi-objective bacterial colony chemotaxis (PMOBCC) algorithm and parallel dichotomy (PD) are applied to run a class of bilevel inverse multi-objective robust optimization (BI-MORO) design. A set of experiments are tested by using different number of MATLAB workers. The results illustrated that it is convenient and effective to use MATLAB for parallelizing the intelligent optimization algorithms.

关键词： parallel computing toolbox MATLAB intel-ligent optimization algorithms robust optimization

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parallel PROGRAMMING IN MATLAB

PARALLEL PROGRAMMING IN MATLAB

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Workshop on Clusters and Computational Grids for Scientific computing

作者： Luszczek, Piotr Univ Tennessee Knoxville TN 37996 USA

关键词： MATLAB parallel computing toolbox multi-core parallel computing parallel programming

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Traveling Salesman Problem Optimization with parallel Genetic Algorithm 23

Traveling Salesman Problem Optimization with Parallel Geneti...

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23nd Signal Processing and Communications Applications Conference (SIU)

作者： Cakir, Murat Yilmaz, Guray Hava Harp Okulu Bilgisayar Muhendisligi Bolumu Istanbul Turkey

ISBN: (纸本)9781467373869

The TSP is a NP-hard problem in optimization studied in both operations research and computer science. Metaheuristics are efficient alternative techniques for NP-hard and greater dimensional problems and they are impossible to solve by classic mathematical techniques. The paper describes the use of MATLAB's parallel computing toolbox for parallel genetic algorithm based design of a TSP. parallel genetic algorithms (PGA) represents a stochastic optimization approach which is computed in co-operating and interconnected computation nodes in a parallel mode. Each node of the PGA can be located on the same processor, or on more processors or on more computers respectively. We also carried on the computation of a TSP example which shows a higher speedup and a better per-formance.

关键词： tsp pga matlab parallel computing toolbox optimization

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On MATLAB experience in accelerating DIRECT-GLce algorithm for constrained global optimization through dynamic data structures and parallelization

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APPLIED MATHEMATICS AND COMPUTATION 2021年 390卷 125596-125596页

作者： Stripinis, Linas Zilinskas, Julius Casado, Leocadio G. Paulavicius, Remigijus Vilnius Univ Inst Data Sci & Digital Technol Akad 4 LT-08663 Vilnius Lithuania Univ Almeria CeiA3 Informat Dept Almeria Spain

In this paper, two different acceleration techniques for a deterministic DIRECT (DIviding RECTangles)-type global optimization algorithm, DIRECT-GLce, are considered. We adopt dynamic data structures for better memory usage in MATLAB implementation. We also study shared and distributed parallel implementations of the original DIRECT-GLce algorithm, and a distributed parallel version for the aggressive counterpart. The efficiency of DIRECT-type parallel versions is evaluated solving box- and generally constrained global optimizations problems with varying complexity, including a practical NASA speed reducer design problem. Numerical results show a good efficiency, especially for the distributed parallel version of the original DIRECT-GLce on a multi-core PC. (C) 2020 Elsevier Inc. All rights reserved.

关键词： DIRECT-type algorithm Derivative-free optimization Dynamic data structures parallel optimization parallel MATLAB parallel computing toolbox

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