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Parallel Newton-Krylov-Schwarz algorithms for the three-dimensional Poisson-Boltzmann equation in numerical simulation of colloidal particle interactions

机译:胶体粒子相互作用数值模拟中的三维Poisson-Boltzmann方程的并行Newton-Krylov-Schwarz算法

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We investigate fully parallel Newton-Krylov-Schwarz (NKS) algorithms for solving the large sparse nonlinear systems of equations arising from the finite element discretization of the three-dimensional Poisson-Boltzmann equation (PBE), which is often used to describe the colloidal phenomena of an electric double layer around charged objects in colloidal and interfacial science. The NKS algorithm employs an inexact Newton method with backtracking (INB) as the nonlinear solver in conjunction with a Krylov subspace method as the linear solver for the corresponding Jacobian system. An overlapping Schwarz method as a preconditioner to accelerate the convergence of the linear solver. Two test cases including two isolated charged particles and two colloidal particles in a cylindrical pore are used as benchmark problems to validate the correctness of our parallel NKS-based PBE solver. In addition, a truly three-dimensional case, which models the interaction between two charged spherical particles within a rough charged micro-capillary, is simulated to demonstrate the applicability of our PBE solver to handle a problem with complex geometry. Finally, based on the result obtained from a PC cluster of parallel machines, we show numerically that NKS is quite suitable for the numerical simulation of interaction between colloidal particles, since NKS is robust in the sense that INB is able to converge within a small number of iterations regardless of the geometry, the mesh size, the number of processors. With help of an additive preconditioned Krylov subspace method NKS achieves parallel efficiency of 71% or better on up to a hundred processors for a 3D problem with 5 million unknowns.
机译:我们研究了完全并行的Newton-Krylov-Schwarz(NKS)算法,用于解决由三维Poisson-Boltzmann方程(PBE)的有限元离散化引起的大型稀疏非线性方程组,该方程通常用于描述胶体现象胶体和界面科学中带电物体周围的双电层的结构。 NKS算法将带有回溯的不精确牛顿法(INB)用作非线性求解器,并使用Krylov子空间方法作为相应雅可比系统的线性求解器。重叠的Schwarz方法作为加速线性求解器收敛的前提。使用两个测试用例(包括两个孤立的带电粒子和两个在圆柱孔中的胶体粒子)作为基准问题,以验证我们基于NKS的并行PBE求解器的正确性。此外,还模拟了一个真实的三维案例,该案例模拟了一个粗糙的带电微毛细管中两个带电球形粒子之间的相互作用,从而证明了我们的PBE求解器可用于处理复杂几何形状的问题。最后,基于从并行计算机的PC群集获得的结果,我们通过数值显示NKS非常适合用于胶体粒子之间相互作用的数值模拟,因为NKS在INB能够收敛于少量整数的意义上是鲁棒的迭代次数,而不管其几何形状,网格大小,处理器数量如何。借助附加的预处理Krylov子空间方法,NKS在具有500万个未知数的3D问题上,在多达100个处理器上的并行效率达到71%或更高。

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