• Title/Summary/Keyword: parallel programming

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Reliability Optimization By using a Nonlinear Programming (비선형계량법(非線型計量法)을 이용한 신뢰성(信賴性)의 최적화(最適化))

  • Lee, Chang-Ho
    • Journal of Korean Society for Quality Management
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    • v.9 no.2
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    • pp.31-36
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    • 1981
  • This paper deals with the reliability optimization of parallel - in - series system subject to several linear constraints. The model of nonlinear constrained optimization is transformed to a saddle point problem by using Lagrange multipliers. Then Newton - Raphson method is used to solve the resulting problem and these step - by - step solution procedures are programmed in Basic Level II of micro - computer TRS-80. An example which has two linear constraints is solved and the results are analyzed.

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EFFICIENT COMPUTATION OF COMPRESSIBLE FLOW BY HIGHER-ORDER METHOD ACCELERATED USING GPU (고차 정확도 수치기법의 GPU 계산을 통한 효율적인 압축성 유동 해석)

  • Chang, T.K.;Park, J.S.;Kim, C.
    • Journal of computational fluids engineering
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    • v.19 no.3
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    • pp.52-61
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    • 2014
  • The present paper deals with the efficient computation of higher-order CFD methods for compressible flow using graphics processing units (GPU). The higher-order CFD methods, such as discontinuous Galerkin (DG) methods and correction procedure via reconstruction (CPR) methods, can realize arbitrary higher-order accuracy with compact stencil on unstructured mesh. However, they require much more computational costs compared to the widely used finite volume methods (FVM). Graphics processing unit, consisting of hundreds or thousands small cores, is apt to massive parallel computations of compressible flow based on the higher-order CFD methods and can reduce computational time greatly. Higher-order multi-dimensional limiting process (MLP) is applied for the robust control of numerical oscillations around shock discontinuity and implemented efficiently on GPU. The program is written and optimized in CUDA library offered from NVIDIA. The whole algorithms are implemented to guarantee accurate and efficient computations for parallel programming on shared-memory model of GPU. The extensive numerical experiments validates that the GPU successfully accelerates computing compressible flow using higher-order method.

Mission Path Planning to Maximize Survivability for Multiple Unmanned Aerial Vehicles based on 3-dimensional Grid Map (3차원 격자지도 기반 생존성 극대화를 위한 다수 무인 항공기 임무경로 계획)

  • Kim, Ki-Tae;Jeon, Geon-Wook
    • IE interfaces
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    • v.25 no.3
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    • pp.365-375
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    • 2012
  • An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for humans. UAVs are currently employed in many military missions and a number of civilian applications. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$_PGA (A-star with Post Smoothing_Parallel Genetic Algorithm) for Multiple UAVs's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and MTSP (Multiple Traveling Salesman Problem). After transforming MRPP into Shortest Path Problem (SPP),$A^*PS$_PGA applies a path planning for multiple UAVs.

Developing a Simulator of the Capture Process in Towed Fishing Gears by Chaotic Fish Behavior Model and Parallel Computing

  • Kim Yong-Hae;Ha Seok-Wun;Jun Yong-Kee
    • Fisheries and Aquatic Sciences
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    • v.7 no.3
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    • pp.163-170
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    • 2004
  • A fishing simulator for towed fishing gear was investigated in order to mimic the fish behavior in capture process and investigate fishing selectivity. A fish behavior model using a psycho-hydraulic wheel activated by stimuli is established to introduce Lorenz chaos equations and a neural network system and to generate the components of realistic fish capture processes. The fish positions within the specified gear geometry are calculated from normalized intensities of the stimuli of the fishing gear components or neighboring fish and then these are related to the sensitivities and the abilities of the fish. This study is applied to four different towed gears i.e. a bottom trawl, a midwater trawl, a two-boat seine, and an anchovy boat seine and for 17 fish species as mainly caught. The Alpha cluster computer system and Fortran MPI (Message-Passing Interface) parallel programming were used for rapid calculation and mass data processing in this chaotic behavior model. The results of the simulation can be represented as animation of fish movements in relation to fishing gear using Open-GL and C graphic programming and catch data as well as selectivity analysis. The results of this simulator mimicked closely the field studies of the same gears and can therefore be used in further study of fishing gear design, predicting selectivity and indoor training systems.

Assistant Professor, Department of Computer Engineering Pukyong Universisty (한국형 방송 프로그램 시스템 디코더 ASSP의 개발)

  • Jo, Gyeong-Yeon
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.5
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    • pp.1229-1239
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    • 1996
  • The increase of additional information broadcasting of TV demands a graphic overlay processor. This paper is about the design, implementation and testing of a graphic overlay processor called by KBPS decoder ASSP (Applicatio n Specific Standard Product) which is compliance with Korea Broadcast Programming System. KBPS decoder ASSP consists of embedded 8 bit microprocessor Z80, graphic overlay controller, KBPS schedule decoder, memory controller, priority interrupt controller, MIDI controller, infrared raccoon receiver, async scrial communication controller, timer, bus controller, universal parallel input-output port and serial-parallel interface. The 0.8 micron CMOS Sea of Gate is used to implement the ASSP in amount of about 31,500 gates, and it is running at 14.318MHz.

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A Path Planning to Maximize Survivability for Unmanned Aerial Vehicle by using $A^*PS$-PGA ($A^*PS$-PGA를 이용한 무인 항공기 생존성 극대화 경로계획)

  • Kim, Ki-Tae;Jeon, Geon-Wook
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.34 no.3
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    • pp.24-34
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    • 2011
  • An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for human. UA V s are currently employed in many military missions such as reconnaissance, surveillance, enemy radar jamming, decoying, suppression of enemy air defense (SEAD), fixed and moving target attack, and air-to-air combat. UAVs also are employed in a number of civilian applications such as monitoring ozone depletion, inclement weather, traffic congestion, and taking images of dangerous territory. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$-PGA (A-star with Post Smoothing-Parallel Genetic Algorithm) for an UAV's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and TSP (Traveling Salesman Problem). A path planning algorithm for UAV is applied by transforming MRPP into SPP (Shortest Path Problem).

Global Internet Computing Environment based on Java (자바를 기반으로 한 글로벌 인터넷 컴퓨팅 환경)

  • Kim, Hui-Cheol;Sin, Pil-Seop;Park, Yeong-Jin;Lee, Yong-Du
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.9
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    • pp.2320-2331
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    • 1999
  • Over the Internet, in order to utilize a collection of idle computers as a parallel computing platform, we propose a new scheme called GICE(Global Internet Computing Environment). GICE is motivated to obtain high programmability, efficient support for heterogeneous computing resources, system scalability, and finally high performance. The programming model of GICE is based on a single address space. GICE is featured with a Java based programming environment, a dynamic resource management scheme, and efficient parallel task scheduling and execution mechanisms. Based on a prototype implementation of GICE, we address the concept, feasibility, complexity and performance of Internet computing.

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Movie Recommendation System using Community Detection and Parallel Programming (커뮤니티 탐지 및 병렬 프로그래밍을 이용한 영화 추천 시스템)

  • Sadriddinov Ilkhomjon;Yixuan Yang;Sony Peng;Sophort Siet;Dae-Young Kim;Doo-Soon Park
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.389-391
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    • 2023
  • In the era of Big Data, humanity is facing a huge overflow of information. To overcome such an obstacle, many new cutting-edge technologies are being introduced. The movie recommendation system is also one such technology. To date, many theoretical and practical kinds of research have been conducted. Our research also focuses on the movie recommendation system by implementing methods from Social Network Analysis(SNA) and Parallel Programming. We applied the Girvan-Newman algorithm to detect communities of users, and a future package to perform the parallelization. This approach not only tries to improve the accuracy of the system but also accelerates the execution time. To do our experiment, we used the MovieLense Dataset.

All Phase Discrete Sine Biorthogonal Transform and Its Application in JPEG-like Image Coding Using GPU

  • Shan, Rongyang;Zhou, Xiao;Wang, Chengyou;Jiang, Baochen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.9
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    • pp.4467-4486
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    • 2016
  • Discrete cosine transform (DCT) based JPEG standard significantly improves the coding efficiency of image compression, but it is unacceptable event in serious blocking artifacts at low bit rate and low efficiency of high-definition image. In the light of all phase digital filtering theory, this paper proposes a novel transform based on discrete sine transform (DST), which is called all phase discrete sine biorthogonal transform (APDSBT). Applying APDSBT to JPEG scheme, the blocking artifacts are reduced significantly. The reconstructed image of APDSBT-JPEG is better than that of DCT-JPEG in terms of objective quality and subjective effect. For improving the efficiency of JPEG coding, the structure of JPEG is analyzed. We analyze key factors in design and evaluation of JPEG compression on the massive parallel graphics processing units (GPUs) using the compute unified device architecture (CUDA) programming model. Experimental results show that the maximum speedup ratio of parallel algorithm of APDSBT-JPEG can reach more than 100 times with a very low version GPU. Some new parallel strategies are illustrated in this paper for improving the performance of parallel algorithm. With the optimal strategy, the efficiency can be improved over 10%.

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.