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可扩展的极化能评估和极化分子动力学中的相关力:二、利用光滑粒子网格 Ewald 实现大规模并行计算。

Scalable evaluation of polarization energy and associated forces in polarizable molecular dynamics: II. Toward massively parallel computations using smooth particle mesh Ewald.

机构信息

Institut du Calcul et de la Simulation, UPMC Univ. Paris 06 , F-75005, Paris, France.

Laboratoire de Chimie Théorique, UPMC Univ. Paris 06, UMR 7617 , F-75005, Paris, France.

出版信息

J Chem Theory Comput. 2015 Jun 9;11(6):2589-99. doi: 10.1021/acs.jctc.5b00171.

Abstract

In this article, we present a parallel implementation of point dipole-based polarizable force fields for molecular dynamics (MD) simulations with periodic boundary conditions (PBC). The smooth particle mesh Ewald technique is combined with two optimal iterative strategies, namely, a preconditioned conjugate gradient solver and a Jacobi solver in conjunction with the direct inversion in the iterative subspace for convergence acceleration, to solve the polarization equations. We show that both solvers exhibit very good parallel performances and overall very competitive timings in an energy and force computation needed to perform a MD step. Various tests on large systems are provided in the context of the polarizable AMOEBA force field as implemented in the newly developed Tinker-HP package, which is the first implementation of a polarizable model that makes large-scale experiments for massively parallel PBC point dipole models possible. We show that using a large number of cores offers a significant acceleration of the overall process involving the iterative methods within the context of SPME and a noticeable improvement of the memory management, giving access to very large systems (hundreds of thousands of atoms) as the algorithm naturally distributes the data on different cores. Coupled with advanced MD techniques, gains ranging from 2 to 3 orders of magnitude in time are now possible compared to nonoptimized, sequential implementations, giving new directions for polarizable molecular dynamics with periodic boundary conditions using massively parallel implementations.

摘要

在本文中,我们提出了一种用于具有周期性边界条件(PBC)的分子动力学(MD)模拟的基于点偶极子的极化力场的并行实现。我们将平滑粒子网格 Ewald 技术与两种最优迭代策略相结合,即预处理共轭梯度求解器和 Jacobi 求解器,以及直接在迭代子空间中进行反演以加速收敛,来求解极化方程。我们展示了这两种求解器在执行 MD 步所需的能量和力计算中都具有非常好的并行性能和整体非常有竞争力的时间。在新开发的 Tinker-HP 包中实现的可极化 AMOEBA 力场的背景下,我们提供了各种大型系统的测试,这是第一个实现可极化模型的方法,该模型使得大规模实验对于大规模并行 PBC 点偶极子模型成为可能。我们表明,使用大量核可以显著加速 SPME 中迭代方法的整体过程,并显著改进内存管理,从而可以访问非常大的系统(数十万原子),因为该算法自然地将数据分布在不同的核上。结合先进的 MD 技术,与非优化的顺序实现相比,现在可以获得 2 到 3 个数量级的时间增益,为使用大规模并行实现的具有周期性边界条件的极化分子动力学提供了新的方向。

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