• Title, Summary, Keyword: Parallel Computing

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A Global Framework for Parallel and Distributed Application with Mobile Objects (이동 객체 기반 병렬 및 분산 응용 수행을 위한 전역 프레임워크)

  • Han, Youn-Hee;Park, Chan-Yeol;Hwang, Chong-Sun;Jeong, Young-Sik
    • Journal of KIISE:Computing Practices and Letters
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    • v.6 no.6
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    • pp.555-568
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    • 2000
  • The World Wide Web has become the largest virtual system that is almost universal in scope. In recent research, it has become effective to utilize idle hosts existing in the World Wide Web for running applications that require a substantial amount of computation. This novel computing paradigm has been referred to as the advent of global computing. In this paper, we implement and propose a mobile object-based global computing framework called Tiger, whose primary goal is to present novel object-oriented programming libraries that support distribution, dispatching, migration of objects and concurrency among computational activities. The programming libraries provide programmers with access, location and migration transparency for distributed and mobile objects. Tiger's second goal is to provide a system supporting requisites for a global computing environment - scalability, resource and location management. The Tiger system and the programming libraries provided allow a programmer to easily develop an objectoriented parallel and distributed application using globally extended computing resources. We also present the improvement in performance gained by conducting the experiment with highly intensive computations such as parallel fractal image processing and genetic-neuro-fuzzy algorithms.

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Performance Analysis of Cluster Network Interfaces for Parallel Computing of Computational Fluid Dynamics (전산유체역학 병렬해석을 위한 클러스터 네트웍 장치 성능분석)

  • Lee, Bo Seong;Hong, Jeong U;Lee, Dong Ho;Lee, Sang San
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.31 no.5
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    • pp.37-43
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    • 2003
  • Parallel computing method is widely used in the computational fluid dynamics for efficient numerical analysis. Nowadays, low cost Linux cluster computers substitute for traditional supercomputers with parallel computing shcemes. The performance of nemerical solvers on an Linux cluster computer is highly dependent not on the performance of processors but on the performance of network devices in the cluster system. In this paper, we investigated the effects of the network devices such as Myrinet2000, gigabit ethernet, and fast ethernet on the performance of the cluster system by using some benchmark programs such as Netpipe, LINPACK, NAS NPB, and MPINS2D Navier-Stokes solvers. Finally, upon this investigation, we will suggest the method for building high performance low cost Linux cluster system in the computational fluid dynamics analysis.

Performance Characterization of Tachyon Supercomputer using Hybrid Multi-zone NAS Parallel Benchmarks (하이브리드 병렬 프로그램을 이용한 타키온 슈퍼컴퓨터의 성능)

  • Park, Nam-Kyu;Jeong, Yoon-Su;Yi, Hong-Suk
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.138-144
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    • 2010
  • Tachyon primary system which introduces recently is a high performance supercomputer that composed with AMD Barcelona nodes. In this paper, we will verify the performance and parallel scalability of TachyonIn by using multi-zone NAS Parallel Benchmark(NPB) which is one of a program with hybrid parallel method. To test performance of hybrid parallel execution, B and C classes of BT-MZ in NPB version 3.3 were used. And the parallel scalability test has finished with Tachyon's 1024 processes. It is the first time in Korea to get a result of hybrid parallel computing calculation using more than 1024 processes. Hybrid parallel method in high performance computing system with multi-core technology like Tachyon describes that it can be very efficient and useful parallel performance benchmarks.

Applying Distributed Agents to Parallel Genetic Algorithm on Dynamic Network Environments (동적 네트워크 환경하의 분산 에이전트를 활용한 병렬 유전자 알고리즘 기법)

  • Baek Jin-Wook;Bang Jeon-Won
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.4
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    • pp.119-125
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    • 2006
  • Distributed Systems can be defined as set of computing resources connected by computer network. One of the most significant techniques in optimization problem domains is parallel genetic algorithms, which are based on distributed systems. Since the status of dynamic network environments such as Internet and mobile computing. can be changed continually, it must not be efficient on the dynamic environments to solve an optimization problem using previous parallel genetic algorithms themselves. In this paper, we propose the effective technique, in which the parallel genetic algorithm can be used efficiently on the dynamic network environments.

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Application of Parallel PSO Algorithm based on PC Cluster System for Solving Optimal Power Flow Problem (PC 클러스터 시스템 기반 병렬 PSO 알고리즘의 최적조류계산 적용)

  • Kim, Jong-Yul;Moon, Kyoung-Jun;Lee, Haw-Seok;Park, June-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.10
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    • pp.1699-1708
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    • 2007
  • The optimal power flow(OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, the OPF problem has been intensively studied and widely used in power system operation and planning. In these days, OPF is becoming more and more important in the deregulation environment of power pool and there is an urgent need of faster solution technique for on-line application. To solve OPF problem, many heuristic optimization methods have been developed, such as Genetic Algorithm(GA), Evolutionary Programming(EP), Evolution Strategies(ES), and Particle Swarm Optimization(PSO). Especially, PSO algorithm is a newly proposed population based heuristic optimization algorithm which was inspired by the social behaviors of animals. However, population based heuristic optimization methods require higher computing time to find optimal point. This shortcoming is overcome by a straightforward parallel processing of PSO algorithm. The developed parallel PSO algorithm is implemented on a PC cluster system with 6 Intel Pentium IV 2GHz processors. The proposed approach has been tested on the IEEE 30-bus system. The results showed that computing time of parallelized PSO algorithm can be reduced by parallel processing without losing the quality of solution.

New GPU computing algorithm for wind load uncertainty analysis on high-rise systems

  • Wei, Cui;Luca, Caracoglia
    • Wind and Structures
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    • v.21 no.5
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    • pp.461-487
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    • 2015
  • In recent years, the Graphics Processing Unit (GPU) has become a competitive computing technology in comparison with the standard Central Processing Unit (CPU) technology due to reduced unit cost, energy and computing time. This paper describes the derivation and implementation of GPU-based algorithms for the analysis of wind loading uncertainty on high-rise systems, in line with the research field of probability-based wind engineering. The study begins by presenting an application of the GPU technology to basic linear algebra problems to demonstrate advantages and limitations. Subsequently, Monte-Carlo integration and synthetic generation of wind turbulence are examined. Finally, the GPU architecture is used for the dynamic analysis of three high-rise structural systems under uncertain wind loads. In the first example the fragility analysis of a single degree-of-freedom structure is illustrated. Since fragility analysis employs sampling-based Monte Carlo simulation, it is feasible to distribute the evaluation of different random parameters among different GPU threads and to compute the results in parallel. In the second case the fragility analysis is carried out on a continuum structure, i.e., a tall building, in which double integration is required to evaluate the generalized turbulent wind load and the dynamic response in the frequency domain. The third example examines the computation of the generalized coupled wind load and response on a tall building in both along-wind and cross-wind directions. It is concluded that the GPU can perform computational tasks on average 10 times faster than the CPU.

A Parallel Iterative Algorithm for Solving The Eigenvalue Problem of Symmetric matrices

  • Baik, Ran
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.4 no.2
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    • pp.99-110
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    • 2000
  • This paper is devoted to the parallelism of a numerical matrix eigenvalue problem. The eigenproblem arises in a variety of applications, including engineering, statistics, and economics. Especially we try to approach the industrial techniques from mathematical modeling. This paper has developed a parallel algorithm to find all eigenvalues. It is contributed to solve a specific practical problem, a vibration problem in the industry. Also we compare the runtime between the serial algorithm and the parallel algorithm for the given problems.

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Optimal Control of Large-Scale Dynamic Systems using Parallel Processing (병렬처리를 이용한 대규모 동적 시스템의 최적제어)

  • Park, Ki-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.5 no.4
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    • pp.403-410
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    • 1999
  • In this study, a parallel algorithm has been developed that can quickly solve the optiaml control problem of large-scale dynamic systems. The algorithm adopts the sequential quadratic programming methods and achieves domain decomposition-type parallelism in computing sensitivities for search direction computation. A silicon wafer thermal process problem has been solved using the algorithm, and a parallel efficiency of 45% has been achieved with 16 processors. Practical methods have also been investigated in this study as a way to further speed up the computation time.

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Development of Mobile Volume Visualization System (모바일 볼륨 가시화 시스템 개발)

  • Park, Sang-Hun;Kim, Won-Tae;Ihm, In-Sung
    • Journal of KIISE:Computing Practices and Letters
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    • v.12 no.5
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    • pp.286-299
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    • 2006
  • Due to the continuing technical progress in the capabilities of modeling, simulation, and sensor devices, huge volume data with very high resolution are common. In scientific visualization, various interactive real-time techniques on high performance parallel computers to effectively render such large scale volume data sets have been proposed. In this paper, we present a mobile volume visualization system that consists of mobile clients, gateways, and parallel rendering servers. The mobile clients allow to explore the regions of interests adaptively in higher resolution level as well as specify rendering / viewing parameters interactively which are sent to parallel rendering server. The gateways play a role in managing requests / responses between mobile clients and parallel rendering servers for stable services. The parallel rendering servers visualize the specified sub-volume with rendering contexts from clients and then transfer the high quality final images back. This proposed system lets multi-users with PDA simultaneously share commonly interesting parts of huge volume, rendering contexts, and final images through CSCW(Computer Supported Cooperative Work) mode.

Parallel Computing Based Design Framework for Multidisciplinary Design Optimization (병렬 컴퓨팅 기반 다분야통합최적설계 지원 설계 프레임워크)

  • Chu, Min-Sik;Lee, Yong-Bin;Lee, Se-Jung;Choi, Dong-Hoon
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.33 no.8
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    • pp.34-41
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    • 2005
  • A parallel computing technique was applied to large scale structure analysis or aerodynamic design and it is a essential element in reducing the huge computation time for large scale design problem. We can use a many computers for reducing the analysis time of multidisciplinary design optimization. But previous MDO frameworks can not support a parallel design process technique so still existing which calls an analysis program continuously. In this paper, We developed a MDO framework(MLR) which supports a parallel design process to solve sequential analysis call. Finally, three sample cases are presented to show the efficiency of design time using the suggested MDO framework.