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A PVM based parallel sparse matrix equation solver to speed up computation of MEI method

机译:基于PVM的并行稀疏矩阵方程求解器可加快MEI方法的计算

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The conventional method of moments is capable of solving wave scattering problems of circumferential dimension of 100 wavelengths. Using the MEI (measured equation of invariance) method the problem of a cylinder of 10,000 wavelengths is within the storage capacity of a personal computer (PC). The MEI method requires the generation of a large sparse matrix for the boundary equations. The MEI matrix coefficients are computed from numerical integrations of the metrons. Interpolation and extrapolation techniques can be employed to save integration time. This means that the solution of the sparse matrix equation of the MEI method is the bottleneck of computation. Since the MEI equation matrix is a sparse matrix with nonzero diagonal elements and very small number of nondiagonal elements at the upper right and lower left corners for 2 dimensional problems, a matrix decomposition algorithm derived by Chen (1973) can be employed for the purpose of decomposition and parallel computing (using parallel virtual machine-PVM).
机译:传统的矩量法能够解决100个波长的周向尺寸的波散射问题。使用MEI(不变性的测量方程)方法,10,000个波长的圆柱体的问题在个人计算机(PC)的存储容量之内。 MEI方法需要为边界方程生成一个大的稀疏矩阵。 MEI矩阵系数是根据节拍的数值积分计算得出的。可以采用内插和外推技术来节省积分时间。这意味着MEI方法的稀疏矩阵方程的解决方案是计算的瓶颈。由于MEI方程矩阵是一个稀疏矩阵,对于二维问题,其对角元素为非零且在右上角和左下角的非对角元素的数量非常少,因此可以采用Chen(1973)导出的矩阵分解算法来实现以下目的:分解和并行计算(使用并行虚拟机-PVM)。

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