• Title, Summary, Keyword: Parallel Computing

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Parallel Computing Simulation of Large-Scale Polymer Electrolyte Fuel Cells (대면적 고분자전해질연료전지의 병렬계산 시뮬레이션)

  • Gwak, Geon-Hui;Chippar, Purushothama;Kang, Kyung-Mun;Ju, Hyun-Chul
    • Transactions of the Korean hydrogen and new energy society
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    • v.22 no.6
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    • pp.868-877
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    • 2011
  • This paper presents a parallel computing methodology for polymer electrolyte fuel cells (PEFCs) and detailed simulation contours of a real-scale fuel cell. In this work, a three-dimensional two-phase PEFC model is applied to a large-scale 200 $cm^2$ fuel cell geometry that requires roughly 13.5 million grid points based on grid-independence study. For parallel computing, the large-scale computational domain is decomposed into 12 sub-domains and parallel simulations are carried out using 12 processors of 2.53 GHz Intel core i7 and 48GB RECC DDR3-1333. The work represents the first attempt to parallelize a two-phase PEFC code and illustrate two-phase contours in a representative industrial cell.

Efficient Parallel TLD on CPU-GPU Platform for Real-Time Tracking

  • Chen, Zhaoyun;Huang, Dafei;Luo, Lei;Wen, Mei;Zhang, Chunyuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.1
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    • pp.201-220
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    • 2020
  • Trackers, especially long-term (LT) trackers, now have a more complex structure and more intensive computation for nowadays' endless pursuit of high accuracy and robustness. However, computing efficiency of LT trackers cannot meet the real-time requirement in various real application scenarios. Considering heterogeneous CPU-GPU platforms have been more popular than ever, it is a challenge to exploit the computing capacity of heterogeneous platform to improve the efficiency of LT trackers for real-time requirement. This paper focuses on TLD, which is the first LT tracking framework, and proposes an efficient parallel implementation based on OpenCL. In this paper, we firstly make an analysis of the TLD tracker and then optimize the computing intensive kernels, including Fern Feature Extraction, Fern Classification, NCC Calculation, Overlaps Calculation, Positive and Negative Samples Extraction. Experimental results demonstrate that our efficient parallel TLD tracker outperforms the original TLD, achieving the 3.92 speedup on CPU and GPU. Moreover, the parallel TLD tracker can run 52.9 frames per second and meet the real-time requirement.

Parallel Nonlinear Analysis of Prestressed Concrete Frame on Cluster System (클러스터 시스템에서 프리스트레스트 콘크리트 프레임의 병렬 비선형해석)

  • 이재석;최규천
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.14 no.3
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    • pp.287-298
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    • 2001
  • Analysis of nonlinear behavior of prestressed concrete frame structures on PC is a time-consuming computing job if the problem size increase to a certain degree. Cluster system has emerged as one of promising computing environments due to its good extendibility, portability, and cost-effectiveness, comparing it with high-end work-stations or servers. In this paper, a parallel nonlinear analysis procedure of prestressed concrete frame structure is presented using cluster computing. Cluster system is configured with readily available pentium III class PCs under Win98 or Linux and fast ethernet. Parallel computing algorithms on element-wise processing parts including the calculation of stiffness matrix, element stresses and determination of material states, check of material failure and calculation of unbalanced loads are developed using MPL. Validity of the method is discussed through typical numerical examples. For the case of 4 node system, maximum speedup is 3.15 and 3.74 for Win98 and Linux, respectively. Important issues for the efficient use of cluster computing system based un PCs and ethernet are addressed.

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Virtual Optimal Design of Satellite Adapter in Parallel Computing Environment (병렬 컴퓨팅 환경 하에서 인공위성 어댑터 가상최적설계)

  • Moon, Jong-Keun;Yoon, Young-Ha;Kim, Kyung-Won;Kim, Sun-Won;Kim, Jin-Hee;Kim, Seung-Jo
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.35 no.11
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    • pp.973-982
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    • 2007
  • In this paper, optimal design framework is developed by automatic mesh generation and PSO(Particle Swarm Optimization) algorithm based on parallel computing environment and applied to structural optimal design of satellite adapter module. By applying automatic mesh generation, it became possible to change the structural shape of adapter module. PSO algorithm was merged with parallel computing environment and for maximizing a computing performance, asynchronous PSO algorithm was developed and could reduce the computing time of optimization process. As constraint conditions, eigen-frequency and maximum stress was considered. Finally using optimal design framework, weight reduction of satellite adapter module is derived with satisfaction of structural safety.

Evaluation of DES key search stability using Parallel Computing (병렬 컴퓨팅을 이용한 DES 키 탐색 안정성 분석)

  • Yoon, JunWeon;Choi, JangWon;Park, ChanYeol;Kong, Ki-Sik
    • Journal of Digital Contents Society
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    • v.14 no.1
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    • pp.65-72
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    • 2013
  • Current and future parallel computing model has been suggested for running and solving large-scale application problems such as climate, bio, cryptology, and astronomy, etc. Parallel computing is a form of computation in which many calculations are carried out simultaneously. And we are able to shorten the execution time of the program, as well as can extend the scale of the problem that can be solved. In this paper, we perform the actual cryptographic algorithms through parallel processing and evaluate its efficiency. Length of the key, which is stable criterion of cryptographic algorithm, judged according to the amount of complete enumeration computation. So we present a detailed procedure of DES key search cryptographic algorithms for executing of enumeration computation in parallel processing environment. And then, we did the simulation through applying to clustering system. As a result, we can measure the safety and solidity of cryptographic algorithm.

A Study on Adaptive Parallel Computability in Many-Task Computing on Hadoop Framework (하둡 기반 대규모 작업처리 프레임워크에서의 Adaptive Parallel Computability 기술 연구)

  • Jik-Soo, Kim
    • Journal of Broadcast Engineering
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    • v.24 no.6
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    • pp.1122-1133
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    • 2019
  • We have designed and implemented a new data processing framework called MOHA(Mtc On HAdoop) which can effectively support Many-Task Computing(MTC) applications in a YARN-based Hadoop platform. MTC applications can be composed of a very large number of computational tasks ranging from hundreds of thousands to millions of tasks, and each MTC application may have different resource usage patterns. Therefore, we have implemented MOHA-TaskExecutor(a pilot-job that executes real MTC application tasks)'s Adaptive Parallel Computability which can adaptively execute multiple tasks simultaneously, in order to improve the parallel computability of a YARN container and the overall system throughput. We have implemented multi-threaded version of TaskExecutor which can "independently and dynamically" adjust the number of concurrently running tasks, and in order to find the optimal number of concurrent tasks, we have employed Hill-Climbing algorithm.

A Basic Study of Thermal-Fluid Flow Analysis Using Grid Computing (그리드 컴퓨팅을 이용한 열유동 해석 기법에 관한 기초 연구)

  • Hong, Seung-Do;Ha, Yeong-Man;Cho, Kum-Won
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.28 no.5
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    • pp.604-611
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    • 2004
  • Simulation of three-dimensional turbulent flow with LES and DNS lakes much time and expense with currently available computing resources and requires big computing resources especially for high Reynolds number. The emerging alternative to provide the required computing power and working environment is the Grid computing technology. We developed the CFD code which carries out the parallel computing under the Grid environment. We constructed the Grid environment by connecting different PC-cluster systems located at two different institutes of Pusan National University in Busan and KISTI in Daejeon. The specification of PC-cluster located at two different institutes is not uniform. We run our parallelized computer code under the Grid environment and compared its performance with that obtained using the homogeneous computing environment. When we run our code under the Grid environment, the communication time between different computer nodes takes much larger time than the real computation time. Thus the Grid computing requires the highly fast network speed.