在SPARC电子结构代码中的本地和半本地密度函数计算的GPU加速
Abhiraj Sharma1, Alfredo Metere1, Phanish Suryanarayana2
1Physics Division, Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
The Journal of chemical physics
|May 30, 2023
概括
我们使用图形处理单元 (GPU) 加快了SPARC电子结构代码,以实现更快的密度函数理论计算. 这种GPU加速显著减少了材料科学模拟的计算时间和资源需求.
科学领域:
- 计算材料科学 计算材料科学
- 量子化学是一种量子化学.
- 高性能计算的高性能计算.
背景情况:
- 密度函数理论 (DFT) 对电子结构计算至关重要.
- 像SPARC这样的实时空间方法为复杂系统提供了优势.
- 计算成本限制了DFT模拟的规模.
研究的目的:
- 开发和实施一个实时空间SPARC代码的图形处理单元 (GPU) 加速版本.
- 为了提高Kohn-Sham密度函数理论 (KS-DFT) 计算的性能.
- 为了减少电子结构模拟所需的计算资源和时间.
主要方法:
- 为NVIDIA GPU开发了一个模块化,基于数学内核的实现.
- 将计算密集型操作卸载到GPU上,将其他操作保留在中央处理单元 (CPU).
- 使用代表性散装和板块模型进行性能评估.
主要成果:
- 与仅CPU执行相比,节点小时达到6倍,核心小时达到60倍的加速度.
- 对于超过 14,000 个电子的金属系统,计算时间减少到 30 秒以下.
- 显著减少了计算资源需求.
结论:
- 对SPARC代码的GPU加速大大提高了DFT的计算效率.
- 开发的实现使得更快,更节省资源的电子结构计算成为可能.
- 这一进步促进了更大,更复杂的材料科学模拟.
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