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PARALLEL STRATEGY OF FMBEM FOR 3D ELASTOSTATICS AND ITS GPU IMPLEMENTATION USING CUDA

机译:FMBEM的3D弹性静力学并行策略及其使用CUDA的GPU实现

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Finite Element Method (FEM) is pervasively used in most of 3D product design analysis, in which Computer Aided Design (CAD) models need to be converted in to mesh models first and then enriched with some material features and boundary conditions data, etc. The interaction between CAD models and FEM models is intensive. Boundary Element Method (BEM) has been expected to be advantageous in large-scale problems in recent years owing to its reduction of the dimensionality and its reduced complexity in mesh generation. However, the BEM application has so far been limited to relatively small problems due to the memory and computational complexity for matrix buildup are O(N~2). The fast multipole BEM (FMBEM) combined with BEM and fast multipole method (FMM) can overcome the defect of the traditional BEM, and provides an effective method to solve the large-scale problem. Combining GPU parallel computing with FMBEM can further improve its efficiency significantly. Based on the three-dimensional elastic mechanics problems, the parallelisms of the multipole moment (ME), multipole moment to multipole moment (M2M) translation, multipole moment to local expansion (M2L) translation, local expansion to local expansion (L2L) translation and near-field direct calculation were analyzed respectively according to the characteristics of the FMM, and the parallel strategies under CUDA were presented in this paper. Three main major parts are included herein: (1) FMBEM theory in 3D elastostatics, (2) the parallel FMBEM algorithm using CUDA, and (3) comparison the GPU parallel FMBEM with BEM, FEM and FMBEM respectively by engineering examples. Numerical example results show the 3D elastostatics GPU FMBEM not only can speed up the boundary element calculation process, but also save memory which can be effective to solve the large-scale engineering problems.
机译:有限元方法(FEM)广泛用于大多数3D产品设计分析中,其中首先需要将计算机辅助设计(CAD)模型转换为网格模型,然后再添加一些材料特征和边界条件数据等。 CAD模型和FEM模型之间的交互非常紧密。由于边界元方法(BEM)的尺寸减小和网格生成的复杂性降低,近年来,边界元方法(BEM)已被认为在大规模问题中具有优势。但是,由于矩阵建立的内存和计算复杂度为O(N〜2),因此BEM应用到目前为止仅限于相对较小的问题。快速多极BEM(FMBEM)与BEM和快速多极方法(FMM)的结合可以克服传统BEM的缺陷,为解决大规模问题提供了有效的方法。将GPU并行计算与FMBEM结合使用可以进一步显着提高其效率。基于三维弹性力学问题,多极矩(ME),多极矩至多极矩(M2M)平移,多极矩至局部膨胀(M2L)平移,局部膨胀至局部膨胀(L2L)平移和根据FMM的特点分别对近场直接计算进行了分析,提出了CUDA下的并行策略。这里包括三个主要部分:(1)3D弹性静力学中的FMBEM理论,(2)使用CUDA的并行FMBEM算法,以及(3)通过工程实例分别比较GPU并行FMBEM与BEM,FEM和FMBEM。数值算例结果表明,3D弹性GPU FMBEM不仅可以加快边界元的计算过程,而且可以节省内存,可以有效地解决大规模工程问题。

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