• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.445-452
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• 2019

In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10a
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• pp.441-443
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• 1998

본 논문은 유무선 환경에서 ATM 멀티캐스트 서비스를 제공하기위한 방안으로서{{{{ { SM}^{2 }A }}}} 를 제안한다. 기존의ATM 멀티캐스트 서비스는 ATM자체의 제약으로 멀티캐스트 서비스가 제한적이며 비효율적이다. 한편, ATM의 중용한 응용으로서 인터넷서비스를 심각하게 고려해야하는데 {{{{ { SM}^{2 }A }}}}는 특히 인터넷 서비스를 제공하는데 적합한 구조를 갖도록 설계되었다.{{{{ { SM}^{2 }A }}}}는 기본적으로 양방향성 공유트리방식인 CBT(Core Based Tree)구조를 갖되 각 지역망 (Regional Network)에서 자체적인 코어스위치( Core Switch)를 보유함으로써 결과적으로 다중 코어 구조를 갖는다. 각 지역망을 잇기 위하여 PNNI 프로토콜을 이용하며 PGL(Peer Group Leader)에 가상 루트(Virtual Root) 및 가상 리프(Virtual Leaf)의 개념을 새로 도입한다. 멀티캐스트 통신의 경우 가장 문제되는 것이 셀끼워넣기(Interleaving)문제인데.{{{{ { SM}^{2 }A }}}}에서는 ITU-T표준 ATC(ATM Transfer Capability)인 ABT/IT(ATM Block Transfer/Immediate Transmission)

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.395-397
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• 2013

MODIS는 기상, 대기, 해양, 그리고 육상 등의 지구전체에 대한 정보를 산출하기 위한 센서로서, 인공위성에 탑재되어 지구관측 데이터를 생산한다. 최초의 MODIS 위성 데이터는 많은 왜곡을 포함하고 있으므로 지형 및 광휘 보정작업은 분석 작업을 하기 위한 필수적인 전처리 작업이다. 위성 데이터 처리를 위해 개발된 SeaDAS는 단일노드/단일코어상에서 수행되기 적합하게 개발되었기 때문에, 대용량의 위성데이터를 전처리하기 위해 많은 시간을 소비해야 한다. 본 논문은 Sun Grid Engine 기반의 다중노드/다중코어를 이용하는 위성 데이터 분산 처리 방법을 제안하고 성능 및 확장성에 대한 평가를 수행한다.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.909-922
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• 2014

This paper reviews Bayesian inference with inequality constraints. It focuses on ⅰ) comparison of models with various inequality/equality constraints on parameters, ⅱ) multiple tests on equalities of parameters when parameters are under inequality constraints, ⅲ) multiple test on equalities of score parameters in models for contingency tables with ordinal categorical variables.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.267-268
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• 2009

많은 컴퓨터들이 기존의 단일코어 컴퓨터에서 벗어나 멀티코어를 장착한 컴퓨터로 변화하는 과정에서 기존의 단일 스레드 프로그래밍에서 다중처리가 중요해지는 세상이 되었다. 이러한 다중처리는 지능로봇 시뮬레이션 교육에 창의적 학습방법을 아주 잘 지원하고 있다. 지능로봇의 형태나 모형 그리고 센서 융합분야에서 동시처리는 중요한 역할을 하고 있다. 본 논문에서는 다중처리 기반 지능로봇 시뮬레이션 환경을 통해 창의적 학습방법에 관한 연구를 제안한다. 무한한 상상력과 창의성을 발휘하여 지능로봇의 모형 설계부터 직접 인공지능 프로그램까지 구현할 수 있는 방법을 소개한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.1-4
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• 2023

운영체제(Operating System)는 사용자의 하드웨어, 시스템 자원(System Resources)을 제어하고 프로그램에 대한 일반적 서비스를 지원하는 시스템 소프트웨어(System Software)이다. 시스템 하드웨어를 관리할 뿐아니라 응용 소프트웨어를 실행하기 위하여 하드웨어 추상화 플랫폼과 공통 시스템 서비스를 제공한다. 최근에는 가상화 기술의 발전에 힘입어 실제 하드웨어가 아닌 가상 머신(HyperVisor) 위에서 실행되기도 한다. 본 연구에서는 다중 코어 프로세서를 타겟으로 한 소규모 운영체제 개발 프로젝트의 일환으로 부트로더를 설계하고 구현하였다. 부팅은 최초 컴퓨터에 전원이 들어온 후 운영체제가 실행할 수 있는 환경을 구축하는데 가장 중요한 역할을 하는 프로그램이며, 이를 잘 활용하면, 임베디드 시스템, IOT 등 다양한 분야에 이용할 수 있다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.679-686
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• 2020

In this thesis, an enhanced method for the feature extraction of vocal source signals and score combination using an MCE-Based weight estimation of the score of multiple feature vectors are proposed for the performance improvement of speaker recognition systems. The proposed feature vector is composed of perceptual linear predictive cepstral coefficients, skewness, and kurtosis extracted with lowpass filtered glottal flow signals to eliminate the flat spectrum region, which is a meaningless information section. The proposed feature was used to improve the conventional speaker recognition system utilizing the mel-frequency cepstral coefficients and the perceptual linear predictive cepstral coefficients extracted with the speech signals and Gaussian mixture models. In addition, to increase the reliability of the estimated scores, instead of estimating the weight using the probability distribution of the convectional score, the scores evaluated by the conventional vocal tract, and the proposed feature are fused by the MCE-Based score combination method to find the optimal speaker. The experimental results showed that the proposed feature vectors contained valid information to recognize the speaker. In addition, when speaker recognition is performed by combining the MCE-based multiple feature parameter scores, the recognition system outperformed the conventional one, particularly in low Gaussian mixture cases.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.6
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• pp.503-512
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• 2018

SAR(Synthetic Aperture Radar) is a technology to acquire images by processing signals obtained from radar, and there is an increasing demand for utilization of high-resolution SAR images. In this paper, for high-speed processing of high-resolution SAR image data, a study for SAR image processing algorithms to achieve optimal performance in multi-core based computer architecture is performed. The performance deterioration due to a large amount of input/output data for high resolution images is reduced by maximizing the memory utilization, and the parallelization ratio of the code is increased by using dynamic scheduling and nested parallelism of OpenMP. As a result, not only the total computation time is reduced, but also the upper bound of parallel performance is increased and the actual parallel performance on a multi-core system with 10 cores is improved by more than 8 times. The result of this study is expected to be used effectively in the development of high-resolution SAR image processing software for multi-core systems with large memory.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.5
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• pp.361-367
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• 2014

In this paper, task scheduling and load balancing methods of multifrontal solution methods of finite element structural analysis in a modern multicore machine are introduced. Many structural analysis problems have generally irregular grid and many kinds of properties and materials. These irregularities and heterogeneities lead to bottleneck of parallelization and cause idle time to analysis. Therefore, task scheduling and load balancing are desired to reduce inefficiency. Several kinds of multithreaded parallelization methods are presented and comparison between static and dynamic task scheduling are shown. To reduce the idle time caused by irregular partitioned subdomains, computational load balancing methods, Balancing all tasks and minmax task pairing balancing, are invented. Theoretical and actual elapsed time are shown and the reason of their performance gap are discussed.

• Journal of KIISE
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• v.44 no.9
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• pp.878-886
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• 2017

This paper discusses performance bottlenecks that may occur when executing high-performance computing MPI applications in the Intel's next generation many-core processor called Knights Landing(KNL), as well as effective resource allocation techniques to solve this problem. KNL is composed of a host processor to enable self-booting in addition to an existing accelerator consisting of a many-core processor, and it was released with a new type of on-package memory with improved bandwidth on top of existing DDR4 based memory. We empirically verified an improvement of the execution performance of multiple MPI applications and the overall system utilization ratio by studying a resource allocation method optimized for such new many-core processor architectures.