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Kohn-Sham 密度泛函理论电子结构计算具有线性缩放的计算时间和内存使用。

Kohn-Sham Density Functional Theory Electronic Structure Calculations with Linearly Scaling Computational Time and Memory Usage.

机构信息

Division of Scientific Computing, Department of Information Technology, Uppsala University, Box 337, SE-751 05 Uppsala, Sweden, and PS Consulting, ul. Zaporoska 8/4, 30-389 Kraków, Poland.

出版信息

J Chem Theory Comput. 2011 Feb 8;7(2):340-50. doi: 10.1021/ct100611z. Epub 2010 Dec 30.

Abstract

We present a complete linear scaling method for hybrid Kohn-Sham density functional theory electronic structure calculations and demonstrate its performance. Particular attention is given to the linear scaling computation of the Kohn-Sham exchange-correlation matrix directly in sparse form within the generalized gradient approximation. The described method makes efficient use of sparse data structures at all times and scales linearly with respect to both computational time and memory usage. Benchmark calculations at the BHandHLYP/3-21G level of theory are presented for polypeptide helix molecules with up to 53 250 atoms. Threshold values for computational approximations were chosen on the basis of their impact on the occupied subspace so that the different parts of the calculations were carried out at balanced levels of accuracy. The largest calculation used 307 204 Gaussian basis functions on a single computer with 72 GB of memory. Benchmarks for three-dimensional water clusters are also included, as well as results using the 6-31G** basis set.

摘要

我们提出了一种完整的线性标度方法,用于混合 Kohn-Sham 密度泛函理论电子结构计算,并展示了其性能。特别关注的是在广义梯度近似下直接以稀疏形式进行 Kohn-Sham 交换相关矩阵的线性标度计算。所描述的方法始终高效地利用稀疏数据结构,并在计算时间和内存使用方面呈线性比例缩放。在 BHandHLYP/3-21G 理论水平上,对具有多达 53250 个原子的多肽螺旋分子进行了基准计算。根据它们对占据子空间的影响选择计算近似的阈值,以使计算的不同部分在平衡的精度水平上进行。最大的计算在一台计算机上使用 307204 个高斯基函数和 72GB 的内存。还包括对三维水分子簇的基准测试,以及使用 6-31G**基组的结果。

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