• 대한전기학회논문지:전력기술부문A
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• 제48권7호
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• pp.909-915
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• 1999

In this paper, we propose an efficient VLSI architecture of Reed-Solomon(RS) decoder. To improve the speed. we develope an architecture featuring parallel and pipelined processing. To implement the parallel and pipelined processing architecture, we analyze the RS decoding algorithm and the honor's algorithm for parallel processing and we also modified the Euclid's algorithm to apply the efficient parallel structure in RS decoder. To show the proposed architecture, the performance of the proposed RS decoder is compared to Shao's and we obtain the 10 % efficiency in area and three times faster in speed when it's compared to Shao's time domain decoder. In addition, we implemented the proposed RS decoder with Altera FPGA Flex10K-50.

• 제어로봇시스템학회논문지
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• 제19권12호
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• pp.1072-1080
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• 2013

In a the present day, many vision inspection techniques are used in productive industrial areas. In particular, in the semiconductor industry the vision inspection system for wafers is a very important system. Also, inspection techniques for semiconductor wafer production are required to ensure high precision and fast inspection. In order to achieve these objectives, parallel processing of the inspection algorithm is essentially needed. In this paper, we propose the GPU (Graphical Processing Unit)-based parallel processing algorithm for the fast inspection of semiconductor wafers. The proposed algorithm is implemented on GPU boards made by NVIDIA Company. The defect detection performance of the proposed algorithm implemented on the GPU is the same as if by a single CPU, but the execution time of the proposed method is about 210 times faster than the one with a single CPU.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2000년도 가을 학술발표회논문집
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• pp.307-314
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• 2000

A parallel condensation algorithm for efficient dynamic analysis of three-dimensional large-scale structures is presented. The algorithm is developed for a user-friendly and cost effective high-performance computing system on a collection of Pentium processors connected via a 100 Mb/s Ethernet LAN. To harness the parallelism in the computing system effectively, a large-scale structure is partitioned into a number of substructures equal to the number of computers in the computing system Then, for reduction in the size of an eigenvalue problem the computations required for static condensation of each substructure is processed concurrently on each slave computer. The performance of th proposed parallel algorithm is demonstrated by applying to dynamic analysis of a three dimensional structure. The results show that how the parallel algorithm facilitates the efficient use of a small number of low-cost personal computers for dynamic analysis of large-scale structures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2761-2781
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• 2018

With the continuous growth of data size and the use of compression technology, data reduction has great research value and practical significance. Aiming at the shortcomings of the existing semantic compression algorithm, this paper is based on the analysis of ItCompress algorithm, and designs a method of bidirectional order selection based on interval partitioning, which named An Optimized Iterative Semantic Compression Algorithm (Optimized ItCompress Algorithm). In order to further improve the speed of the algorithm, we propose a parallel optimization iterative semantic compression algorithm using GPU (POICAG) and an optimized iterative semantic compression algorithm using Spark (DOICAS). A lot of valid experiments are carried out on four kinds of datasets, which fully verified the efficiency of the proposed algorithm.

• 대한전기학회논문지:전력기술부문A
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• 제54권8호
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• pp.375-387
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• 2005

This paper presents an application of parallel Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution systems. The main objective of service restoration of distribution systems is, when a fault or overload occurs, to restore as much load as possible by transferring the do-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints, which is a combinatorial optimization problem. This problem has many constraints with many local minima to solve the optimal switch position. This paper develops parallel GA-TS algorithm for service restoration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solutions of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper $10\%$ of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC cluster system consists of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through ethernet switch based fast ethernet. To show the validity of the proposed method, proposed algorithm has been tested with a practical distribution system in Korea. From the simulation results, we can find that the proposed algorithm is efficient for the distribution system service restoration in terms of the solution quality, speedup, efficiency and computation time.

• 대한전기학회논문지:전력기술부문A
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• 제53권10호
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• pp.556-564
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• 2004

This paper presents an application of parallel Genetic Algorithm-Tabu Search(GA-TS) algorithm to search an optimal solution of a reconfiguration in distribution system. The aim of the reconfiguration of distribution systems is to determine switch position to be opened for loss minimization in the radial distribution systems, which is a discrete optimization problem. This problem has many constraints and very difficult to solve the optimal switch position because it has many local minima. This paper develops parallel GA-TS algorithm for reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10% of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node aster predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium Ⅳ CPU and is connected with others through ethernet switch based fast ethernet. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution systems in the reference paper. From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution qualify. speedup. efficiency and computation time.

• KIEE International Transactions on Power Engineering
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• 제5A권2호
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• pp.116-124
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• 2005

This paper presents an application of the parallel Genetic Algorithm-Tabu Search (GA- TS) algorithm, and that is to search for an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration of distribution systems is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to solve the optimal switch position because of its numerous local minima. This paper develops a parallel GA- TS algorithm for the reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10$\%$ of the population to enhance the local searching capabilities. With migration operation, the best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based rapid Ethernet. To demonstrate the usefulness of the proposed method, the developed algorithm was tested and is compared to a distribution system in the reference paper From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution quality, speedup, efficiency, and computation time.

• 한국정보과학회논문지:시스템및이론
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• 제30권10호
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• pp.586-594
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• 2003

X-Match 알고리즘은 비교적 간단하여 하드웨어로 구현하는 데에 적합한 무손실 압축 알고리즘이다. X-Match 알고리즘은 사이클 당 32비트의 압축이 가능하므로 고속 압축에 적합하다. 그렇지만 버스 폭이 증가됨에 따라서 이에 맞추어서 압축 단위를 증가시킬 필요가 있게 되었다. 본 논문에서는 X-Match 알고리즘을 병렬로 수행하여 압축 속도를 2배 향상시키고 X-Match 알고리즘 거의 비슷한 압축률을 제공하는 협동 병렬 X-Match 알고리즘, 즉 X-MatchCP 알고리즘을 제안한다. 기존의 병렬 X-Match 알고리즘이 X-Match 알고리즘을 병렬로 수행할 매에 각자의 사전을 검색하는 데 비해서 X-MatchCP 알고리즘에서는 X-Match 알고리즘이 병렬로 수행되지만 전체 사전을 검색하여 매칭빈도를 높이도록 하였고 run-length 부호화도 두 워드에 대해서 한꺼번에 하는 방식으로 서로 협동하면서 동작한다 메모리 데이타와 파일 자료를 사용한 시뮬레이션 결과 X-MatchCP 알고리즘은 같은 사전 크기의 X-Match 알고리즘과 거의 비슷한 압축률을 보였다. 그리고 X-MatchCP 알고리즘의 하드웨어 구현을 위한 전체적인 구조 설계를 Verilog 언어를 사용하여 수행하였다.

• 한국전자파학회논문지
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• 제25권3호
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• pp.357-364
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• 2014

본 연구에서는 빠르게 전자파 해석을 수행할 수 있는 병렬 유한차분 시간영역(Finite-Difference Time-Domain: FDTD) 알고리즘을 구현하기 위하여 CPU 클러스터를 구축하였다. 병렬 FDTD 알고리즘은 단일 프로세서를 이용한 FDTD 알고리즘에 비해 해석 시간을 크게 줄일 수 있으며, 전기적으로 매우 큰 구조물에 대한 전자파 해석도 가능하다. 본 연구팀에서는 CPU 클러스터 기반의 병렬 FDTD 알고리즘에서 요구되는 프로세스 간의 통신을 위해 MPI(Message Passing Interface) 라이브러리를 이용하였으며, 3차원 공간분할을 적용하여 프로세스 간의 통신 시간을 최소화하였다. 단일 프로세서를 이용한 FDTD 알고리즘 대비 CPU 클러스터 기반의 병렬 FDTD 알고리즘의 계산속도 향상도를 기본 모드와 하이퍼 모드에서 분석하였으며, 전기적으로 매우 큰 콘크리트 구조물의 전자파 해석을 하였다.

• 전기학회논문지
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• 제67권5호
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• pp.656-662
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• 2018

Pattern matching algorithm is widely used in many application fields such as bio-informatics, intrusion detection, etc. Among many string matching algorithms, KMP (Knuth-Morris-Pratt) algorithm is commonly used because of its fast execution time when using large texts. However, the processing speed of KMP algorithm is also limited when the text size increases significantly. In this paper, we propose a high throughput parallel KMP algorithm considering CPU-GPU memory hierarchy based on OpenCL in GPGPU (General Purpose computing on Graphic Processing Unit). We focus on the optimization for the allocation of work-times and work-groups, the local memory copy of the pattern data and the failure table, and the overlapping of the data transfer with the string matching operations. The experimental results show that the execution time of the optimized parallel KMP algorithm is about 3.6 times faster than that of the non-optimized parallel KMP algorithm.