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首页> 外文期刊>The Journal of Chemical Physics >Extension and evaluation of the multilevel summation method for fast long-range electrostatics calculations
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Extension and evaluation of the multilevel summation method for fast long-range electrostatics calculations

机译:多级求和方法的扩展和评估,用于快速远程静电计算

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Several extensions and improvements have been made to the multilevel summation method (MSM) of computing long-range electrostatic interactions. These include pressure calculation, an improved error estimator, faster direct part calculation, extension to non-orthogonal (triclinic) systems, and parallelization using the domain decomposition method. MSM also allows fully non-periodic long-range electrostatics calculations which are not possible using traditional Ewald-based methods. In spite of these significant improvements to the MSM algorithm, the particle-particle particle-mesh (PPPM) method was still found to be faster for the periodic systems we tested on a single processor. However, the fast Fourier transforms (FFTs) that PPPM relies on represent a major scaling bottleneck for the method when running on many cores (because the many-to-many communication pattern of the FFT becomes expensive) and MSM scales better than PPPM when using a large core count for two test problems on Sandia's Redsky machine. This FFT bottleneck can be reduced by running PPPM on only a subset of the total processors. MSM is most competitive for relatively low accuracy calculations. On Sandia's Chama machine, however, PPPM is found to scale better than MSM for all core counts that we tested. These results suggest that PPPM is usually more efficient than MSM for typical problems running on current high performance computers. However, further improvements to MSM algorithm could increase its competitiveness for calculation of long-range electrostatic interactions.
机译:对计算远程静电相互作用的多级求和方法(MSM)进行了一些扩展和改进。其中包括压力计算,改进的误差估计器,更快的直接零件计算,扩展到非正交(三斜)系统以及使用域分解方法进行并行化。 MSM还允许使用传统的基于Ewald的方法无法进行的完全非周期性的远距离静电计算。尽管对MSM算法进行了重大改进,但对于我们在单个处理器上测试的周期性系统,仍然发现使用粒子-粒子-粒子-网格(PPPM)方法更快。但是,PPPM所依赖的快速傅里叶变换(FFT)代表了该方法在许多内核上运行时的主要缩放瓶颈(因为FFT的多对多通信模式变得昂贵),并且在使用时,MSM的缩放性优于PPPM Sandia的Redsky机器上的两个测试问题的核心数量很大。通过仅在全部处理器的一个子集上运行PPPM可以减少FFT瓶颈。 MSM在精度相对较低的计算中最具竞争力。但是,在Sandia的Chama机器上,对于我们测试的所有核心数量,发现PPPM的伸缩性都比MSM好。这些结果表明,对于在当前高性能计算机上运行的典型问题,PPPM通常比MSM更有效。但是,对MSM算法的进一步改进可以提高其在远程静电相互作用计算中的竞争力。

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