swMATH ID: 7164
Software Authors: Wu, S.C.; Zhang, H.O.; Zheng, C.; Zhang, J.H.
Description: A high performance large sparse symmetric solver for the meshfree Galerkin method One main disadvantage of meshfree methods is that their memory requirement and computational cost are much higher than those of the usual finite element method (FEM). This paper presents an efficient and reliable solver for the large sparse symmetric positive definite (SPD) system resulting from the element-free Galerkin (EFG) approach. A compact mathematical model of heat transfer problems is first established using the EFG procedure. Based on the widely used Successive Over-Relaxation-Preconditioned Conjugate Gradient (SSOR-PCG) scheme, a novel solver named FastPCG is then proposed for solving the SPD linear system. To decrease the computational time in each iteration step, a new algorithm for realizing multiplication of the global stiffness matrix by a vector is presented for this solver. The global matrix and load vector are changed in accordance with a special rule and, in this way, a large account of calculation is avoided on the premise of not decreasing the solution’s accuracy. In addition, a double data structure is designed to tackle frequent and unexpected operations of adding or removing nodes in problems of dynamic adaptive or moving high-gradient field analysis. An information matrix is also built to avoid drastic transformation of the coefficient matrix caused by the initial-boundary values. Numerical results show that the memory requirement of the FastPCG solver is only one-third of that of the well-developed AGGJE solver, and the computational cost is comparable with the traditional method with the increas of solution scale and order.
Homepage: http://www.worldscientific.com/doi/abs/10.1142/S0219876208001613
Keywords: large sparse symmetric linear system; meshfree methods; heat transfer analysis; preconditioned conjugate gradient method; double data form
Related Software: AGGJE; CUDA; LAPACK
Cited in: 4 Publications

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