• 충청수학회지
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• 제10권1호
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• pp.147-159
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• 1997

It is important to solve the large sparse linear system appeared in many application field such as $AA^Ty={\beta}$ efficiently. In solving this linear system, the sparse solver using the splitting method for the relatively dense column is experimentally better than the direct solver using the Cholesky method.

• ETRI Journal
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• 제29권4호
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• pp.524-526
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• 2007

In this letter, we study the multicast protection problem in sparse-splitting wavelength-division multiplexing (WDM) optical network, and propose a novel multicast protection algorithm called the shared source-leaf path-based protection (SLPP) algorithm. Unlike the proposals in previous studies, the backup paths derived by SLPP can share wavelength with the primary tree in sparse-splitting WDM networks. Simulations are used to evaluate the effectiveness of the SLPP algorithm.

• 대한기계학회논문집B
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• 제30권1호
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• pp.8-15
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• 2006

A Sparse Point Representation(SPR) based on interpolation wavelets is presented. The SPR is implemented for the purpose of CFD data compression. Unlike conventional wavelet transformation, the SPR relieves computing workload in the similar fashion of lifting scheme that includes splitting and prediction procedures in sequence. However, SPR skips update procedure that is major part of lifting scheme. Data compression can be achieved by proper thresholding method. The advantage of the SPR method is that, by keeping even point physical values, low frequency filtering procedure is omitted and its related unphysical thresholing mechanism can be avoided in reconstruction process. Extra singular feature detection algorithm is implemented for preserving singular features such as shock and vortices. Several numerical tests show the adequacy of SPR for the CFD data. It is also shown that it can be easily extended to nonlinear adaptive wavelets for enhanced feature capturing.

• 대한수학회지
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• 제36권1호
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• pp.209-227
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• 1999

We propose new parallel block ILU (Incomplete LU) factorization preconditioners for a nonsymmetric block-tridiagonal M-matrix. Theoretial properties of these block preconditioners are studied to see the convergence rate of the preconditioned iterative methods, Lastly, numerical results of the right preconditioned GMRES and BiCGSTAB methods using the block ILU preconditioners are compared with those of these two iterative methods using a standard ILU preconditioner to see the effectiveness of the block ILU preconditioners.

• 대한기계학회논문집B
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• 제40권9호
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• pp.597-604
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• 2016

본 연구에서는 GPU를 이용한 비압축성 유동장의 병렬연산을 위하여, P2P1 유한요소를 이용한 분리 알고리즘 내의 행렬 해법인 이중공액구배법(Bi-Conjugate Gradient)의 CUDA 기반 알고리즘을 개발하였다. 개발된 알고리즘을 이용해 비대칭 협착관 유동을 해석하고, 단일 CPU와의 계산시간을 비교하여 GPU 병렬 연산의 성능 향상을 측정하였다. 또한, 비대칭 협착관 유동 문제와 다른 행렬 패턴을 가지는 유체구조 상호작용 문제에 대하여 이중공액구배법 내의 희소 행렬과 벡터의 곱에 대한 GPU의 병렬성능을 확인하였다. 개발된 코드는 희소 행렬의 1개의 행과 벡터의 내적을 병렬 연산하는 커널(Kernel)로 구성되며, 최적화는 병렬 감소 연산(Parallel Reduction), 메모리 코얼레싱(Coalescing) 효과를 이용하여 구현하였다. 또한, 커널 생성 시 워프(Warp)의 크기에 따른 성능 차이를 확인하였다. 표준예제들에 대한 GPU 병렬연산속도는 CPU 대비 약 7배 이상 향상됨을 확인하였다.