Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
J Chem Phys. 2021 Feb 7;154(5):054112. doi: 10.1063/5.0040966.
Particle Mesh Ewald (PME) has become a standard method for treating long-range electrostatics in molecular simulations. Although the method has inferior asymptotic computational complexity to its linear scaling competitors, it remains enormously popular due to its high efficiency, which stems from the use of fast Fourier transforms (FFTs). This use of FFTs provides great challenges for scaling the method up to massively parallel systems, in large part because of the need to transfer large amounts of data. In this work, we demonstrate that this data transfer volume can be greatly reduced as a natural consequence of the structure of the PME equations. We also suggest an alternative algorithm that supplants the FFT with a linear algebra approach, which further decreases communication costs at the expense of increased asymptotic computational complexity. This linear algebra based approach is demonstrated to have great potential for latency hiding by interleaving communication and computation steps of the short- and long-range electrostatic terms.
粒子网格 Ewald(PME)方法已经成为处理分子模拟中长程静电的标准方法。尽管该方法的渐近计算复杂度劣于其线性标度竞争对手,但由于其高效率,仍然非常流行,这源于快速傅里叶变换(FFT)的使用。这种 FFT 的使用为将该方法扩展到大规模并行系统带来了巨大的挑战,部分原因是需要传输大量的数据。在这项工作中,我们证明了由于 PME 方程的结构,这种数据传输量可以大大减少。我们还提出了一种替代算法,用线性代数方法取代 FFT,这进一步降低了通信成本,但以增加渐近计算复杂度为代价。通过交错短程和长程静电项的通信和计算步骤,这种基于线性代数的方法具有很好的潜在延迟隐藏能力。