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Block constrained versus generalized Jacobi preconditioners for iterative solution of large-scale Biot's FEM equations

机译:块约束与广义Jacobi预处理器用于大规模Biot FEM方程的迭代解

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摘要

Generalized Jacobi (GJ) diagonal preconditioner coupled with symmetric quasi-minimal residual (SQMR) method has been demonstrated to be efficient for solving the 2 x 2 block linear system of equations arising from discretized Biot's consolidation equations. However, one may further improve the performance by employing a more sophisticated non-diagonal preconditioner. This paper proposes to employ a block constrained preconditioner P_c that uses the same 2 x 2 block matrix but its (1, 1) block is replaced by a diagonal approximation. Numerical results on a series of 3-D footing problems show that the SQMR method preconditioned by P_c is about 55% more efficient time-wise than the counterpart preconditioned by GJ when the problem size increases to about 180,000 degrees of freedom. Over the range of problem sizes studied, the P_c-preconditioned SQMR method incurs about 20% more memory than the GJ-precon-ditioned counterpart. The paper also addresses crucial computational and storage issues in constructing and storing P_c efficiently to achieve superior performance over GJ on the commonly available PC platforms.
机译:事实证明,广义Jacobi(GJ)对角前置条件预处理器与对称拟最小残差(SQMR)方法相结合可有效解决离散化Biot固结方程引起的2 x 2块线性方程组。然而,可以通过采用更复杂的非对角预调节器来进一步提高性能。本文提出采用块约束预处理器P_c,该预处理器使用相同的2 x 2块矩阵,但其(1,1)块被对角线近似替代。关于一系列3-D基础问题的数值结果表明,当问题大小增加到约18万自由度时,由P_c预处理的SQMR方法在时间上的效率比由GJ预处理的对应方法高约55%。在研究的问题大小范围内,P_c预处理的SQMR方法比GJ预处理的同类方法多产生约20%的内存。本文还解决了关键的计算和存储问题,这些问题在有效地构造和存储P_c方面要达到在通用PC平台上优于GJ的性能。

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