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副矩阵和GPU加速实现密度矩阵紧密结合.

Abylay Katbashev1, Robert Schade2, Michael Lass2,3

  • 1Mulliken Center for Theoretical Chemistry, Institute for Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4, 53115 Bonn, Germany.

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概括
此摘要是机器生成的。

我们使用图形处理单元 (GPU) 和子矩阵方法开发了更快的紧密结合计算. 这加快了大型系统的模拟,使先进的计算材料科学更容易获得.

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科学领域:

  • 计算材料科学科学 计算材料科学
  • 量子化学 是一个量子化学.
  • 固态物理 固态物理

背景情况:

  • 像Hartree-Fock和DFT这样的单粒子理论面临着由于自相一致场 (SCF) 程序的立方缩放的计算限制.
  • 没有先进的算法和硬件,大规模应用是不切实际的.
  • 在这个领域,PTB紧固结合潜力是关键的方法.

研究的目的:

  • 实施和评估GPU加速和子矩阵方法用于PTB紧密结合潜力.
  • 克服传统SCF程序的计算瓶.
  • 为了实现更大,更复杂的材料系统的模拟.

主要方法:

  • 与密度矩阵净化方法对比传统的基于对角化的SCF溶解器.
  • 实施一种分解类型的子矩阵方法,以实现高效的计算.
  • 使用图形处理单元 (GPU) 进行加速计算.
  • 系统大小和计算机硬件的系统变化.

主要成果:

  • GPU 加速实现了 10-15 倍的性能提速,使更大的系统的模拟成为可能.
  • 亚矩阵方法减少了大约10^4基础函数的系统的计算成本.
  • 通过子矩阵方法保持了可接受的数值准确性.

结论:

  • GPU 加速和子矩阵方法的结合显著提高了紧密结合计算的效率.
  • 这项工作推动了计算材料科学中可行的系统大小的边界.
  • 这些发现强调了硬件-算法相互作用对未来发展的重要性.