Many applications from geosciences require simulations of seismic waves in porous media. Biot's theory of poroelasticity describes the coupling between solid and fluid phases and introduces a stiff source term, thereby increasing computational cost and motivating efficient methods utilising High-Performance Computing. We present a novel realisation of the discontinuous Galerkin scheme with Arbitrary DERivative time stepping (ADER-DG) that copes with stiff source terms. To integrate this source term with a reasonable time step size, we use an element-local space-time predictor, which needs to solve medium-sized linear systems - with 1000 to 10000 unknowns - in each element update (i.e., billions of times). We present a novel block-wise back-substitution algorithm for solving these systems efficiently. In comparison to LU decomposition, we reduce the number of floating-point operations by a factor of up to 25. The block-wise back-substitution is mapped to a sequence of small matrix-matrix multiplications, for which code generators are available to generate highly optimised code. We verify the new solver thoroughly in problems of increasing complexity. We demonstrate high-order convergence for 3D problems. We verify the correct treatment of point sources, material interfaces and traction-free boundary conditions. In addition, we compare against a finite difference code for a newly defined layer over half-space problem. We find that extremely high accuracy is required to resolve the slow P-wave at a free surface, while solid particle velocities are not affected by coarser resolutions. By using a clustered local time stepping scheme, we reduce time to solution by a factor of 6 to 10 compared to global time stepping. We conclude our study with a scaling and performance analysis, demonstrating our implementation's efficiency and its potential for extreme-scale simulations.
翻译:地球科学的许多应用都需要在多孔介质中模拟地震波。 Biot 的分子弹性理论描述了固态和流态阶段之间的混合,并引入了一个硬源术语,从而增加计算成本,鼓励高效使用高性能计算器。我们展示了一种新颖的不连续的Galerkin计划,它与任意的Derivative时间阶(ADER-DG)相匹配。为了将这一源术语与合理的时间步调相融合,我们使用了一个元素-本地空间时序预测器,它需要解决中等规模的线性系统-1000至1000个未知的每个元素更新(即数十亿次 ) 。 我们展示了一种新型的后补算法算法来高效解决这些系统。 与LU decomption 相比, 我们将浮点操作的数量降低到25 。 块偏偏偏偏偏偏偏偏偏偏偏偏偏偏偏的后变法多变法, 我们发现我们可以用代码来生成高度精确的时间代码 。 我们核查新的溶解的直径直径直径直径直径直方的直径直方的直径分析, 我们用直径直径直方的直的直的直方的直方的直方的直方的直方的直方的直方的直方的直径直方的直方的直方的直方的直方的直方的直方的直方的直方的直方的直方的直方的直方的直方, 。