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Introducing DDEC6 atomic population analysis: part 4. Efficient parallel computation of net atomic charges, atomic spin moments, bond orders, and more

机译:介绍DDEC6原子种群分析:第4部分。净原子收费的高效并行计算,原子旋转时刻,债券订单等等

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The DDEC6 method is one of the most accurate and broadly applicable atomic population analysis methods. It works for a broad range of periodic and non-periodic materials with no magnetism, collinear magnetism, and non-collinear magnetism irrespective of the basis set type. First, we show DDEC6 charge partitioning to assign net atomic charges corresponds to solving a series of 14 Lagrangians in order. Then, we provide flow diagrams for overall DDEC6 analysis, spin partitioning, and bond order calculations. We wrote an OpenMP parallelized Fortran code to provide efficient computations. We show that by storing large arrays as shared variables in cache line friendly order, memory requirements are independent of the number of parallel computing cores and false sharing is minimized. We show that both total memory required and the computational time scale linearly with increasing numbers of atoms in the unit cell. Using the presently chosen uniform grids, computational times of similar to 9 to 94 seconds per atom were required to perform DDEC6 analysis on a single computing core in an Intel Xeon E5 multiprocessor unit. Parallelization efficiencies were usually >50% for computations performed on 2 to 16 cores of a cache coherent node. As examples we study a B-DNA decamer, nickel metal, supercells of hexagonal ice crystals, six X@C-60 endohedral fullerene complexes, a water dimer, a Mn-12-acetate single molecule magnet exhibiting collinear magnetism, a Fe4O12N4C40H52 single molecule magnet exhibiting non-collinear magnetism, and several spin states of an ozone molecule. Efficient parallel computation was achieved for systems containing as few as one and as many as >8000 atoms in a unit cell. We varied many calculation factors (e.g., grid spacing, code design, thread arrangement, etc.) and report their effects on calculation speed and precision. We make recommendations for excellent performance.
机译:DDEC6方法是最准确和广泛适用的原子种群分析方法之一。它适用于多种周期性和非周期性材料,无磁性,共线磁性和非共线磁性,而不管基于型型。首先,我们向DDEC6电荷分配分配净原子费用对应于求解一系列14拉格朗人。然后,我们为整体DDEC6分析,旋转分区和键订单计算提供流程图。我们写了一个openmp并行化fortran代码,以提供有效的计算。我们表明,通过将大阵列存储为缓存线友好订单中的共享变量,内存要求与并行计算核的数量无关,并且最小化虚假共享。我们表明,随着单位单元中的原子数增加,所需的总存储器和计算时间尺度线性尺度。使用目前所选择的均匀网格,需要每次出色的计算时间来对英特尔Xeon E5多处理器单元中的单个计算核心进行DDEC6分析。对于高速缓存相干节点的2至16个核心执行的计算,平行化效率通常> 50%。作为我们研究B-DNA焊接器,镍金属,六方冰晶的超级细胞,六x×@ C-60腹皮富勒烯配合物,水二聚体,呈CON-12-醋酸单分子磁体,表现出共线磁,Fe4O12N4C40H52单分子磁铁表现出非共线磁性,以及臭氧分子的几种旋转状态。对于在单元电池中含有少量和多达> 8000原子的系统实现了有效的并行计算。我们改变了许多计算因素(例如,网格间距,代码设计,线程排列等),并报告它们对计算速度和精度的影响。我们提出了出色的表现建议。

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  • 来源
    《RSC Advances》 |2018年第5期|共30页
  • 作者单位

    New Mexico State Univ Dept Chem &

    Mat Engn Las Cruces NM 88003 USA;

    New Mexico State Univ Dept Chem &

    Mat Engn Las Cruces NM 88003 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 化学;
  • 关键词

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