• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1121-1130
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• 2004

The Genetic Algorithm (GA), an optimization technique based on the theory of natural selection, has proven to be a relatively robust means of searching for global optimum. It converges to the global optimum point without auxiliary information such as differentiation of function. In the case of a complex problem, the GA involves a large population number and requires a lot of computing time. To improve the process, this research used parallel processing with several personal computers. Parallel process technique is classified into two methods according to subpopulation's size and number. One is the fine-grained method (FGM), and the other is the coarse-grained method (CGM). This study selected the CGM as a parallel process technique because the load is equally divided among several computers. The given design domain should be reduced according to the degree of feasibility, because mechanical system problems have constraints. The reduced domain is used as an initial design domain. It is consistent with the feasible domain and the infeasible domain around feasible domain boundary. This parallel process used the Message Passing Interface library.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.169-176
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• 1994

This paper describes an efficient parallel evaluation algorithm for accelerating fault simulation, which can be applied to combinational circuits. The method is based on a combination of all the advantages in parallel, deductive and concurrent schemes in terms of evaluation and propagation of fautly gates for achieving high performance and handling multi-valued signal. We also propose a new fault grouping procedure to increase parallel operation of fault bits by packing active faults which occur in the same signal line densely into the same fault group. The algorithm has been implemented in C language on a Sun 3/260, and experimental results for ISCAS'85 benchmark circuits have been shown that this algorithm is 2.6 to 8.2 times faster than the conventional cocurrent fault simulation algorithm.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.587-595
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• 2008

Parallel coordinate plot of Inselberg (1985) is useful for visualizing dozens of variables, but so far the plot's applicability is limited to the variables of numerical type. The aim of this study is to extend the parallel coordinate plot so that it can accommodate both numerical and categorical variables. We combine Hayashi's (1950, 1952) quantification method of categorical variables and Hurley's (2004) endlink algorithm of ordering variables for the parallel coordinate plot. In line with our former study (Kwak and Huh, 2008), we develop Andrews' type modification of conventional straight-lines parallel coordinate plot to visualize the mixed-type data.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.7
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• pp.735-741
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• 1992

This paper presents a parallel algorithm for the finite element analysis using relatively inexpensive transputer parallel system. The substructure method, which is highly parallel in nature, is used to improve the parallel computing efficiency by splitting up the whole structure into substructures. The proposed algorithm is applied to a simple two-dimensional magnetostatic problem. It is found that the more the number of transputer is increased, the more the total computation time is reduced. And the computational efficiency becomes better as the number of internal boundary nodes becomes smaller.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.24-30
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• 1996

The ray tracing method, which is one of many photorealistic rendering techniques, requires heavy computational processing to synthesize images. Parallel processing can be used to reduce the computational processing time. A parallel algorithm for the ray tracing has been implemented and executed for various images on transputer systems. In order to develop a scalable parallel algorithm, a processor farming technique has been exploited. Since each image is divided and distributed to each farming processor, the scalability of the parallel system and load balancing are achieved naturally in the proposed algorithm. Efficiency of the parallel algorithm is obtained up to 95% for nine processors. However, the best size of a distributed task is much higher in simple images due to less computational requirement for every pixel. Efficiency degradation is observed for large granularity tasks because of load unbalancing caused by the large task. Overall, transputer systems behave as good scalable parallel processing system with respect to the cost-performance ratio.

• The Journal of Natural Sciences
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• v.5 no.2
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• pp.39-43
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• 1992

Detection of parallelism by a compiler is very desirable from a user's point of view. However, even the most sophisticated techniques to detect parallelism trip on trivial impediments, such as conditionals, function calls, and input/output statements, fail to detect most of the parallelism present in a program. Some parallelizing compilers provide feedback to the user when they have difficulty in deciding about parallel execution. Under these circumstances, a programmer has to restructure the source code to aid the detection of parallelism. But, functional and declarative languages can be said to offer many advantages in this context. Functional programs are easier to reason about because their output is determinate, that is, independent of the order of evaluation. However, functional languages traditionally have lacked good facilities for manipulating arrays and matrices. In this paper, a declarative language called Id has been proposed as a solution to some of these problems.

• Journal of Korea Game Society
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• v.10 no.5
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• pp.95-102
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• 2010

This paper proposes a parallel algorithm of the flocking behaviors using GPU. To do this, we used CUDA as the parallel processing architecture of GPU and then analyzed its characteristics and constraints. Based on them, the paper improved the performance by parallelizing to find the neighbors for an agent which requires the largest cost in the flocking behaviors. We implemented the proposed algorithm on GTX 285 GPU and compared experimentally its performance with the original spatial partitioning method. The results of the comparison showed that the proposed algorithm outperformed the original method up to 9 times with respect to the execution time.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.13 no.1
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• pp.13-20
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• 2009

The IPSAP which is a finite element analysis program has been developed for high parallel performance computing. This program consists of various analysis modules - stress, vibration and thermal analysis module, etc. The M orthogonal block Lanczos algorithm with shiftinvert transformation is used for solving eigenvalue problems in the vibration module. And the multifrontal algorithm which is one of the most efficient direct linear equation solvers is applied to factorization and triangular system solving phases in this block Lanczos iteration routine. In this study, the performance enhancement procedures of the IPSAP are composed of the following stages: 1) communication volume minimization of the factorization phase by modifying parallel matrix subroutines. 2) idling time minimization in triangular system solving phase by partial inverse of the frontal matrix and the LCM (least common multiple) concept.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.10
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• pp.1057-1065
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• 1990

A parallel processing algorithm for the discrete Kalman filter, which is one of the most commonly used filtering techniques in modern control, signal processing, and communication, is proposed. To decrease the number of computations critical in the Kalman filter, previously proposed parallel algorithms are of the hierarchical structure by distributed processing of measurements, or of the systolic structure to disperse the computational burden. In this paper, a new parallel Kalman filter employing a structure similar to recursive doubling is proposed. Estimated valuse of state variables by the new algorithm converge faster to the true values because the new algorithm can process data twice faster than the conventional Kalman filter. Moreover, it maintains the optimality of the conventional Kalman filter.

• The Transactions of the Korea Information Processing Society
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• v.1 no.3
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• pp.290-298
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• 1994

In this paper we propose parallel sorting algorithm, taking 0( $n^{n}$ log n) time complexity, 0( $n^{x}$ log n) cost (parallel running time * number of processors) and 0( $n^{1-}$x＋ $n^{x}$ )data movement complexity under the ERWW- PRAM model. The methods for solving these problems similar. Parallel algorithm finds pivot for partitioning the data into ordered subsets of approximately equal size by using encording pointers..