• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1688-1695
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• 2008

Recently, it is common in a distribution system of Korea Electric Power Corporation (KEPCO) to find instances where distribution lines are parallel. A traditional method of an induced voltage calculation is not suitable for parallel distribution lines. For more actual analysis of induced voltage on telecommunication lines in parallel distribution lines, a new calculation method is needed. This paper presents a new calculation method of an induced voltage on telecommunication line using equivalent ${\pi}$ circuits matrix in parallel distribution lines. The advantages of the calculation method are using actual neutral current value and not using screening factor for considering the overhead ground wire and the neutral wire. To verify the effectiveness and the accuracy of the method, various case studies are performed with EMTP(Electro-Magnetic Transients Program).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1649-1665
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• 2021

In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.61-68
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• 2001

A parallel nonlinear analysis program of prestressed concrete frame is migrated on a PC cluster system and a massively parallel processing system, CRAY T3E system, using MPI. The PC cluster system is configured with Pentium Ⅲ class PCs and fast ethernet. The CRAY T3E system is composed of a set of nodes each containing one Processing Element (PE), a memory subsystem and its distributed memory interconnect network. Parallel computing algorithms are implemented 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. Parallel performance of the migrated program is evaluated through typical numerical examples.

• Journal of Power System Engineering
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• v.16 no.4
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• pp.12-16
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• 2012

In this paper, the equations of motions for planar multibody dynamics are established for considering the parallel programming based on GPU. Cartesian coordinates are used to formulate the equations of motion and implicit integration method called HHT-alpha is employed. Open chain multibody system is considered for computer simulation. CUDA toolkit is employed for establishing the GPU parallel programming. The exactness of the analysis is verified from the comparison with ADAMS. The results from parallel computing based on GPU are compared with the results from the sequential programming based on CPU in terms of calculation time. The multiple pendulum with bodies and joints is employed for the computer simulation. In the pendulum system that has 290 bodies, the parallel program indicates an improved efficiency of about 25.5 second(15.5% improvement). It is noted that the larger the size of system is, the time efficiency is better.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.20 no.7
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• pp.9-16
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• 2015

This paper proposes the parallel design of a shot change detection algorithm using frame segmentation and moving blocks. In the proposed approach, the high parallel processing components, such as frame histogram calculation, block histogram calculation, Otsu threshold setting function, frame moving operation, and block histogram comparison, are designed in parallel for NVIDIA GPU. In order to minimize memory access delay time and guarantee fast computation, the output of a GPU kernel becomes the input data of another kernel in a pipeline way using the shared memory of GPU. In addition, the optimal sizes of CUDA processing blocks and threads are estimated through the prior experiments. In the experimental test of the proposed shot change detection algorithm, the detection rate of the GPU based parallel algorithm is the same as that of the CPU based algorithm, but the average of processing time speeds up about 6~8 times.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.719-722
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• 2003

This paper presents the development of reservoir characterization model equipped with parallelized genetic algorithm, and its application for a heterogeneous reservoir system with integration of the well data and multi-phase production data. A parallel processing method performed by PC-cluster was applied to the developed model in order to reduce time for an inverse calculation. By utilizing the developed model, we performed the inverse calculation with the production data obtained from three layered reservoir system to estimate porosity and permeability distribution. As a result, the pressures observed at well almost identical to those calculated by the developed model. Also, it was confirmed that parallel processing could be applied for reservoir characterization study efficiently.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.194-198
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• 2011

In this study, an efficient algorithm for Delaunay triangulation of a number of points which can be used on a GPU-based parallel computation is studied The developed algorithm is programmed using CUDA library. and the program takes full advantage of parallel computation which are concurrently performed on each of the threads on GPU. The results of partitioned triangulation collected from the GPU computation requires proper stitching between neighboring partitions and calculation of connectivities among triangular cells on CPU In this study, the effect of number of threads on the efficiency and total duration for Delaunay grid generation is studied. And it is also shown that GPU computing using CUDA for Delaunay grid generation is feasible and it saves total time required for the triangulation of the large number points compared to the sequential CPU-based triangulation programs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.133-142
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• 2012

In this paper, we propose and implement a high-speed algorithm for CGH that is to calculate digital hologram by modeling the interference phenomenon for tow lights. This algorithm changes the computation equations into a parallel-computable ones and implements it with a structure consisting of two kinds of cells (initial calculation cell, and update calculation cell). The parallel computation algorithm is to get the rest hologram pixels concurrently after calculation the first hologram column. Here, the initial calculation cells compute the first column of the hologram and the update calculation cells compute the rest of the hologram. The two kinds of cells performs a pipeline operation to complete the operations of the two cells at the same time. A CGH calculator to compute the hole hologram for a light source is structured by arranging the two kinds of cells. Results from simulation showed that the maximum operation frequency is about 215MHz. So, experiments are performed by setting this frequency and the same environments as the method showing the best performance. As the results, the proposed one could complete the computation of 81.75 CGH frames per second, while the previous method computes 62.9 CGH frames per second.

• ETRI Journal
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• v.31 no.4
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• pp.387-392
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• 2009

This paper introduces a novel parallel shift operator finite-difference time-domain (SO-FDTD) method for plasma in the dispersive media. We calculate the interaction between the electromagnetic wave of various frequencies and non-magnetized plasma by using the parallel SO-FDTD method. Then, we compare the results，which are calculated with serial and parallel SO-FDTD executions to obtain the speedup ratio and validate the parallel execution. We conclude that the parallel SO method has almost the same precision as the serial SO method, while the parallel approach expands the scope of memory and reduces the CPU time.