Multilevel summation for dispersion: a linear-time algorithm for r(-6) potentials.
Multilevel summation for dispersion: a linear-time algorithm for r(-6) potentials.
复制标题
色散的多级求和：r(-6) 势的线性时间算法。
DOI：
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复制
发表时间：
2013
影响因子：
4.4
通讯作者：
A. Ismail
中科院分区：
文献类型：
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作者：
Daniel Tameling;P. Springer;P. Bientinesi;A. Ismail
我们扩展了多级求和（MLS）方法，该方法最初是为了在分子动力学模拟中评估长程库仑相互作用而开发的[R。D.斯基尔岛Tezcan和D. J.哈代，J.计算机。23，673（2002）]，以处理分散体相互作用。虽然色散势在形式上是短程的，但精确计算界面和非均匀系统中的力和能量需要长程方法。与粒子-粒子、粒子-网格和光滑粒子网格埃瓦尔德方法相比，MLS方法具有一些显著的优点。与基于网格的Ewald方法不同，MLS不使用快速傅立叶变换，因此不受通信和带宽问题的限制。此外，与基于网格的Ewald方法的O（NlogN）复杂度相比，它在粒子数上线性缩放。虽然MLS方法的结构对于不同的势是不变的，但是每个算法步骤都必须适应色散相互作用的r（-6）形式。此外，我们已经推导出误差界，类似于由哈代[“用于生物分子模拟的力的快速评估的多级求和”，Ph.D.论文，伊利诺伊大学厄巴纳-香槟分校，2006年]的静电MLS。使用原型实现，我们已经证明了线性缩放的MLS方法的分散，目前的结果建立的方法的准确性和效率。
We have extended the multilevel summation (MLS) method, originally developed to evaluate long-range Coulombic interactions in molecular dynamics simulations [R. D. Skeel, I. Tezcan, and D. J. Hardy, J. Comput. Chem. 23, 673 (2002)], to handle dispersion interactions. While dispersion potentials are formally short-ranged, accurate calculation of forces and energies in interfacial and inhomogeneous systems require long-range methods. The MLS method offers some significant advantages compared to the particle-particle particle-mesh and smooth particle mesh Ewald methods. Unlike mesh-based Ewald methods, MLS does not use fast Fourier transforms and is thus not limited by communication and bandwidth concerns. In addition, it scales linearly in the number of particles, as compared with the O(NlogN) complexity of the mesh-based Ewald methods. While the structure of the MLS method is invariant for different potentials, every algorithmic step had to be adapted to accommodate the r(-6) form of the dispersion interactions. In addition, we have derived error bounds, similar to those obtained by Hardy ["Multilevel summation for the fast evaluation of forces for the simulation of biomolecules," Ph.D. thesis, University of Illinois at Urbana-Champaign, 2006] for the electrostatic MLS. Using a prototype implementation, we have demonstrated the linear scaling of the MLS method for dispersion, and present results establishing the accuracy and efficiency of the method.
DOI：
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发表时间：
2006
期刊：
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影响因子：
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作者：
David J. Hardy
通讯作者：
David J. Hardy