• Proceedings of the KIEE Conference
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• 2001.07e
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• pp.134-140
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• 2001

Parallel processing has the potential to be cost effectively used on computationally intense power system problems. But this technology is not still available is not only parallel computer but also parallel processing scheme. Testing these algorithms to ensure accuracy, and evaluation of their performance is also an issue. Although a significant amount of parallel algorithms of power system problem have been developed in last decade, actual testing on processor architectures lies in the beginning stages. This paper presents the parallel processing algorithm to supply the base being able to treat power flow by newton's method by the distributed memory type parallel computer. This method is to assign and to compute teared blocks of sparse matrix at each parallel processors. The testing to insure accuracy of developed method have been done on serial computer by trying to simulate a parallel environment.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.2
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• pp.55-59
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• 2002

Parallel processing is able to be used effectively on computationally intense power system problems. But this technology is not still available is not only parallel computer but also parallel processing scheme. Testing these algorithms to ensure accuracy, and evaluation of their performance is also an issue. Although a significant amount of parallel algorithms of power system problem have been developed in last decade, actual testing on parallel computer architectures lies in the beginning stages because no clear cut paths. This paper presents Jacobian modeling method to supply the base being able to treat power flow by newton's method by the computer. This method is to assign and to compute teared blocks of sparse matrix at each parallel processors. The testing to insure accuracy of developed method have been done on serial computer by trying to simulate a parallel environment.

• Journal of IKEEE
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• v.18 no.3
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• pp.398-402
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• 2014

In this paper, we propose a parallel processing method of pedestrian detection algorithm based on ROI-CENTRIST. There is a difficulty in the real-time processing of pedestrian detection in the embedded environment, using the conventional pedestrian detection method. This problem can be solved by a parallel processing method of applying the ROI to the conventional algorithm. The proposed parallel processing method of pedestrian detection using ROI-CENTRIST show the result of 5.2 frames per second, which is about 10% improvement over the conventional pedestrian detection method based on CENTRIST.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1963-1970
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• 2001

It is essential design process to analyze processing method and set out top level HW configuration using main parameters before implementation of the SAR processor. This paper identifies the impact of the I/O and algorithm structure upon the parallel processing to be assessed and suggests the practical mapping method fur parallel processing to the SAR data. Also, simulation is performed to the E-SAR processor to examine the usefulness of the method, and the results are analyzed and discussed.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.3
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• pp.83-89
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• 2015

Connected component labeling (CCL) is a mandatory step in image segmentation where objects are extracted and uniquely labeled. CCL is a computationally expensive operation and thus is often done in parallel processing framework to reduce execution time. Various parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method, modified 8 directional label selection (M8DLS) method, HYBRID1 method, and HYBRID2 method. Soh et al. showed that HYBRID2 outperforms the others and is the best so far. In this paper we propose a new hybrid parallel CCL algorithm termed as HYBRID3 that combines selective four directional label search (S4DLS) with label backtracking (LB). We show that the average percentage speedup of the proposed over M8DLS is around 60% more than that of HYBRID2 over M8DLS for various kinds of images.

• ETRI Journal
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• v.31 no.5
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• pp.510-517
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• 2009

A high throughput parallel decoding method is developed for context-based adaptive variable length codes. In this paper, several new design ideas are devised and implemented for scalable parallel processing, a reduction in area, and a reduction in power requirements. First, simplified logical operations instead of memory lookups are used for parallel processing. Second, the codes are grouped based on their lengths for efficient logical operation. Third, up to M bits of the input stream can be analyzed simultaneously. For comparison, we designed a logical-operation-based parallel decoder for M=8 and a conventional parallel decoder. High-speed parallel decoding becomes possible with our method. In addition, for similar decoding rates (1.57 codes/cycle for M=8), our new approach uses 46% less chip area than the conventional method.

• Journal of Mechanical Science and Technology
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• v.16 no.5
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• pp.609-618
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• 2002

In practical designs, most of the multidisciplinary problems have a large-size and complicate design system. Since multidisciplinary problems have hundreds of analyses and thousands of variables, the grouping of analyses and the order of the analyses in the group affect the speed of the total design cycle. Therefore, it is very important to reorder and regroup the original design processes in order to minimize the total computational cost by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and by processing them in parallel. In this study, a new decomposition method is proposed for parallel processing of multidisciplinary design optimization, such as collaborative optimization (CO) and individual discipline feasible (IDF) method. Numerical results for two example problems are presented to show the feasibility of the proposed method.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.401-404
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• 2017

The 360 VR video has a format of a stereoscopic shape such as an isometric shape or a cubic shape or a cubic shape. Although these formats have different characteristics, they have in common that the resolution is higher than that of a normal 2D video. Therefore, it takes much longer time to perform coding/decoding on 360 VR video than 2D Video, so parallel processing techniques are essential when it comes to coding 360 VR video. HEVC, the state of art 2D video codec, uses Wavefront Parallel Processing (WPP) technology as a standard for parallelization. This technique is optimized for 2D videos and does not show optimal performance when used in 3D videos. Therefore, a suitable method for WPP is required for 3D video. In this paper, we propose WPP coding/decoding method which improves WPP performance on cube map format 3D video. The experiment was applied to the HEVC reference software HM 12.0. The experimental results show that there is no significant loss of PSNR compared with the existing WPP, and the coding complexity of 15% to 20% is further reduced. The proposed method is expected to be included in the future 3D VR video codecs.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.293-298
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• 2021

In general, the guided weapon seeker and the guided control device process the target, search, recognition, and capture information to indicate the state of the guided missile, and play a role in controlling the operation and control of the guided weapon. The signals required for guided weapons are gaze change rate, visual signal, and end-stage fuselage orientation signal. In order to process the complex and difficult-to-process missile signals of recent missiles in real time, it is necessary to increase the data processing speed of the missiles. This study showed the processing speed after applying the stop and go and inverse enumeration algorithm among the parallel algorithm methods of PINQ and comparing the processing speed of the signal data required for the guided missile in real time using the guided missile inspection program. Based on the derived data processing results, we propose an effective method for processing missile data when applying a parallel processing algorithm by comparing the processing speed of the multi-core processing method and the single-core processing method, and the CPU core utilization rate.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.488-495
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• 2009

This paper presents a fast feature extraction method for autonomous mobile robots utilizing parallel processing and based on OpenMP, SSE (Streaming SIMD Extension) and CUDA programming. In the first step on CPU version, the algorithms and codes are optimized and then implemented by parallel processing. The parallel algorithms are debugged to maintain the same level of performance and the process for extracting key points and obtaining dominant orientation with respect to key points is parallelized. After extraction, a parallel descriptor via SSE instructions is constructed. And the GPU version also implemented by parallel processing using CUDA based on the SIFT. The GPU-Parallel descriptor achieves an acceleration up to five times compared with the CPU-Parallel descriptor, but it shows the lower performance than CPU version. CPU version also speed-up the four and half times compared with the original SIFT while maintaining robust performance.