• Title/Summary/Keyword: Jacobi Iterative Method

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TWO-LAYER MUTI-PARAMETERIZED SCHWARZ ALTERNATING METHOD

  • Kim, Sang-Bae
    • Journal of applied mathematics & informatics
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    • v.9 no.1
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    • pp.101-124
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    • 2002
  • The convergence rate of a numerical procedure barred on Schwarz Alternating Method (SAM) for solving elliptic boundary value problems (BVP's) depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It hee been observed that the Robin condition(mixed interface condition), controlled by a parameter, can optimize SAM's convergence rate. Since the convergence rate is very sensitive to the parameter, Tang[17] suggested another interface condition called over-determined interface condition. Based on the over-determined interface condition, we formulate the two-layer multi-parameterized SAM. For the SAM and the one-dimensional elliptic model BVP's, we determine analytically the optimal values of the parameters. For the two-dimensional elliptic BVP's , we also formulate the two-layer multi-parameterized SAM and suggest a choice of multi-parameter to produce good convergence rate .

Development and Applications on Power Electronic Circuit Analysis Program PECAP (전력전자회로 해석프로그램 PECAP 개발과 응용)

  • 정태경;차귀수;함송엽
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.32 no.10
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    • pp.335-340
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    • 1983
  • The analysis of static power converter circuit using state-space method is presented. Semiconductors are modeled in two-state resistors depending on their ON or OFF states. Then the modes of circuit are determined according to the conducting states of semiconductors and different describing matrices are given automatically for each mode. Newton-Raphson algorithm is used as an iterative method for obtaining steady-state solution and an adjoint network is introduced for the efficient and accurate evaluation of the Jacobi matrix in the algorithm. Using the porogram exploited from the above algorithm, it is shown through examples that the results are in good agreement with the analytic solutions and computation time is considerably reduced for obtaining the steady-state solutions.

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AN ASSESSMENT OF PARALLEL PRECONDITIONERS FOR THE INTERIOR SPARSE GENERALIZED EIGENVALUE PROBLEMS BY CG-TYPE METHODS ON AN IBM REGATTA MACHINE

  • Ma, Sang-Back;Jang, Ho-Jong
    • Journal of applied mathematics & informatics
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    • v.25 no.1_2
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    • pp.435-443
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    • 2007
  • Computing the interior spectrum of large sparse generalized eigenvalue problems $Ax\;=\;{\lambda}Bx$, where A and b are large sparse and SPD(Symmetric Positive Definite), is often required in areas such as structural mechanics and quantum chemistry, to name a few. Recently, CG-type methods have been found useful and hence, very amenable to parallel computation for very large problems. Also, as in the case of linear systems proper choice of preconditioning is known to accelerate the rate of convergence. After the smallest eigenpair is found we use the orthogonal deflation technique to find the next m-1 eigenvalues, which is also suitable for parallelization. This offers advantages over Jacobi-Davidson methods with partial shifts, which requires re-computation of preconditioner matrx with new shifts. We consider as preconditioners Incomplete LU(ILU)(0) in two variants, ever-relaxation(SOR), and Point-symmetric SOR(SSOR). We set m to be 5. We conducted our experiments on matrices from discretizations of partial differential equations by finite difference method. The generated matrices has dimensions up to 4 million and total number of processors are 32. MPI(Message Passing Interface) library was used for interprocessor communications. Our results show that in general the Multi-Color ILU(0) gives the best performance.

Two dimensional variable-length vector storage format for efficient storage of sparse matrix in the finite element method (유한요소법에서 희소행렬의 효율적인 저장을 위한 2차원 가변길이 벡터 저장구조)

  • Boo, Hee-Hyung;Kim, Sung-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.9
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    • pp.9-16
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    • 2012
  • In this paper, we propose the two dimensional variable-length vector storage format which can be used for efficient storage of sparse matrix in the FEM (finite element method). The proposed storage format is the method storing only actual needed non-zero values of each row on upper triangular matrix with the total rows N, by using two dimensional variable-length vector instead of $N{\times}N$ large sparse matrix of entire equation of finite elements. This method only needs storage spaces of the number of minimum 1 to maximum 5 in 2D grid structure and the number of minimum 1 to maximum 14 in 3D grid structure of analysis target. The number doesn't excess two times although involving index number. From the experimental result, we can find out that the proposed storage format can reduce the memory space more effectively, as the total number of nodes increases, than the existing skyline storage format storing maximum column height.