pyRMG: 超级计算机上高通量,大细胞DFT计算的框架
Ryan Morelock1, Soumendu Bagchi1, Emil Briggs2
1Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA.
The Journal of chemical physics
|February 6, 2026
概括
pyRMG是一个新的Python包,使实空间多网格 (RMG) 密度函数理论 (DFT) 计算更容易获得. 它可以在极大尺寸的计算机上进行高效,大规模的材料模拟,用户输入最小.
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.
- 高性能计算 高性能计算
背景情况:
- 超大规模计算为化学模拟提供了前所未有的力量.
- 实空间多网格 (RMG) 密度函数理论 (DFT) 代码在数千个处理器 (GPU) 上显示出出色的可扩展性.
- 有限的工作流基础设施阻碍了采用RMG-DFT代码.
研究的目的:
- 开发一个用户友好的Python包,pyRMG,以简化RMG-DFT计算.
- 提高大规模材料模拟的可访问性和自动化.
- 在领导级计算平台上使用RMG-DFT促进高通量研究.
主要方法:
- 开发了pyRMG,这是一个Python包,集成了pymatgen和ASE.
- 自动输入生成和对RMG-DFT的收检查.
- 集成的pyRMG与现代任务调度器 (例如,Flux) 集成的pyRMG用于超级平台 (边境,珀尔穆特).
主要成果:
- 证明了pyRMG在高通量DFT研究中的能力.
- 在2D2L-Bi2Se3/2L-NbSe2异构结构中成功分析了应变效应.
- 展示了基于RMG的工作流程,在有限的用户干预下趋同.
结论:
- pyRMG显著降低了使用可扩展的RMG-DFT方法的进入壁垒.
- 该软件包在先进的计算架构上实现了高效的,自动化的材料发现和分析.
- pyRMG使研究人员能够更轻松,更快速地进行复杂的模拟.
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