• Annual Conference of KIPS
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• 2014.11a
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• pp.336-339
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• 2014

전자제품의 스마트화 열풍으로 임베디드 시스템의 하드웨어 및 소프트웨어의 발전이 경쟁적으로 이루어지고 있지만, 하드웨어 발전 속도에 비해 그 활용도는 미진한 편이다. 특히, 스마트 TV 는 대형 스크린을 갖고 있다는 장점이 있고, 사물인터넷 시대의 중추 역할을 할 것으로 기대되기 때문에 많은 계산의 신속한 처리를 요구 받을 가능성이 크다. 따라서 본 논문에서는 webOS 기반 스마트 TV 에서, 계산자원을 충분한 활용하기 위한 병렬처리 가능성을 확인하고자 webOS 시스템을 프로파일링하고 그 결과를 분석하였다.

• Annual Conference of KIPS
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• 2019.10a
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• pp.137-140
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• 2019

교통 시뮬레이션 시스템은 현실 세계의 교통 및 차량 관련 데이터를 기반으로 미래의 차량 움직임을 예측하는 프로그램으로, 다양한 교통문제를 해결을 위한 도구가 될 수 있다. 시뮬레이션 스케일을 전국단위로 확장하기 위해서 분산/병렬 시스템을 도입해야 하는데, 이 논문에서는 병렬/분산 과정에서 핵심이 되는 Open MPI 기반의 데이터 교환에 대한 방법을 제안하고자 한다. 공통된 하나의 커뮤니케이션 모듈을 기반으로 분산된 노드의 데이터 교환에 대한 문제를 해결하여 생산성을 높이고, 시뮬레이션 과정에서 소요되는 커뮤니케이션 타임을 줄여줄 것으로 예상된다.

• Annual Conference of KIPS
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• 2010.04a
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• pp.966-968
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• 2010

컴퓨팅 자원의 확보가 용이해짐에 따라 이러한 자원을 최대한 활용하려는 시도가 늘어나고 있다. 시스템을 검사하는 정형적 기법으로써 많이 사용되고 있는 모델 체킹은 상태폭발 문제를 완화하기 위해서 여러 컴퓨팅 자원을 한꺼번에 사용하려는 연구가 이루어져 왔다. 하지만 이 기법 역시 여러 상태 모델들이 하나로 합쳐지면서 여전히 상태폭발 문제를 발생 시킨다. 본 논문에서는 이러한 문제가 나타나는 원인을 지적하고 이를 해결하기 위해 모델 체킹의 기본 요소인 새로운 병렬적 도달성 분석 기법을 제시한다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.81-87
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• 2013

In this paper, we present an implementation of Long Term Evolution (LTE) Uplink (UL) system on a Software Defined Radio (SDR) platform using a conventional Personal Computer (PC), which adopts Graphic Processing Units (GPU) and Universal Software Radio Peripheral2 (USRP2) with URSP Hardware Driver (UHD) for SDR software modem and Radio Frequency (RF) transceiver, respectively. We have adopted UHD because UHD provides flexibility in the design of transceiver chain. Also, Cognitive Radio (CR) engine have been implemented by using libraries from UHD. Meanwhile, we have implemented the software modem in our system on GPU which is suitable for parallel computing due to its powerful Arithmetic and Logic Units (ALUs). From our experiment tests, we have measured the total processing time for a single frame of both transmit and receive LTE UL data to find that it takes about 5.00ms and 6.78ms for transmit and receive, respectively. It particularly means that the implemented system is capable of real-time processing of all the baseband signal processing algorithms required for LTE UL system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.357-364
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• 2014

In this work, we construct a CPU cluster to implement a parallel finite-difference time domain(FDTD) algorithm for fast electromagnetic analyses. This parallel FDTD algorithm can reduce the computational time significantly and also analyze electrically larger structures, compared to a single FDTD counterpart. The parallel FDTD algorithm needs communication between neighboring processors, which is performed by the MPI(Message Passing Interface) library and a 3-D domain decomposition is employed to decrease the communication time between neighboring processors. Compared to a single-processor FDTD, the speed up factor of a-CPU-cluster-based parallel FDTD algorithm is investigated for the normal mode and the hypermode and finally analyze an electrically large concrete structure by the developed parallel algorithm.

• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.253-260
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• 2001

It is important to detect races for debugging shared-memoy parallel programs, because the races cause unintended nondeterministic program execution. Previous on-the-fly techniques to detect races can not guarantee the first race detection in nested parallel programs. Detecting the first race is important for debugging parallel programs, since the removal of the first race may make the next occurred races disappear. In this paper, we presents an on-the-fly detection technique to detect all of the first races through the reexecution of the debugged programs. We assume that the debugged parallel program may have one-way nested parallel programs. The number of reexecution is at the least the nesting depth of the program in the worst case. The space complexity is O(VT) and the time complexity to detect race in each access of access history is O(T), where V is number of shared variables and T is the maximum parallelism of the program. This efficiency of our technique in each execution is the same with the previous on-the-fly detection techniques. Therefore, this technique makes debugging parallel programs more effective and practical.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.7
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• pp.791-797
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• 2014

In order to create an environment for Apache Hadoop for parallel distributed processing system of Bigdata, by connecting a plurality of computers, or to configure the node, using the configuration of the virtual nodes on a single computer it is necessary to build a cloud fading environment. However, be constructed in practice for education in these systems, there are many constraints in terms of cost and complex system configuration. Therefore, it is possible to be used as training for educational institutions and beginners in the field of Bigdata processing, development of learning systems and inexpensive practical is urgent. Based on the Raspberry Pi board, training and analysis of Big data processing, such as Hadoop and NoSQL is now the design and implementation of a learning system of parallel distributed processing of possible Bigdata in this study. It is expected that Bigdata parallel distributed processing system that has been implemented, and be a useful system for beginners who want to start a Bigdata and education.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.61-66
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• 2002

A fuzzy control strategy is described which is utilized to control the joint angle and tip deflection in single flexible manipulator. In this paper, an existing model for a single flexible manipulator is used for the initial development of an FLC. One FLC is designed to govern the joint angle of the manipulator as it is rotated from one position to another, and the second FLC is designed to attenuate the tip deflection which result from joint angle body motion. Reference Trajectory Command is an important method to reduce vibration in flexible beam. This paper presents a very simple command control shaping which eliminates multiple mode residual vibration in a flexible beam combined parallel fuzzy controller. The effectiveness of proposed scheme is demonstrated through computer simulation.

• Annual Conference of KIPS
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• 2018.05a
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• pp.469-470
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• 2018

Object tracking is a common task in computer vision, an essential part of various vision-based applications. After several years of development, object tracking in video is still a challenging problem because of various visual properties of objects and surrounding environment. Particle filter is a well-known technique among common approaches, has been proven its effectiveness in dealing with difficulties in object tracking. However, particle filter is a high-complexity algorithms, which is an severe disadvantage because object tracking algorithms are required to run in real time. In this research, we utilize parallel programming to accelerate particle filter-based object tracking algorithms. Experimental results showed that our approach reduced the execution time significantly.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.4 no.2
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• pp.369-378
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• 2014

The Reed-Muller code is one of the efficient algorithms for multiple bit error correction, however, its high-computation requirement inherent in the decoding process prohibits its use in practical applications. To solve this problem, this paper proposes a graphics processing unit (GPU)-based parallel error control approach using Reed-Muller R(r, m) coding for real-time wireless communication systems. GPU offers a high-throughput parallel computing platform that can achieve the desired high-performance decoding by exploiting massive parallelism inherent in the algorithm. In addition, we compare the performance of the GPU-based approach with the equivalent sequential approach that runs on the traditional CPU. The experimental results indicate that the proposed GPU-based approach exceedingly outperforms the sequential approach in terms of execution time, yielding over 70× speedup.