在SPARC电子结构代码中的混合功能计算的GPU加速.
Xin Jing1,2, Abhiraj Sharma3, John E Pask3
1College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
The Journal of chemical physics
|May 8, 2025
概括
我们使用图形处理单元 (GPU) 加快了电子结构计算. 这种GPU加速代码显著减少了密度函数理论中混合函数计算的计算时间和资源.
科学领域:
- 计算物理学的计算物理.
- 材料科学是一种材料科学.
- 量子化学是一种量子化学.
背景情况:
- 电子结构计算对于理解材料特性至关重要.
- 密度函数理论中的混合函数计算在计算上要求很高.
- 加快这些计算可以实现更大,更复杂的模拟.
研究的目的:
- 开发一个图形处理单元 (GPU) 加速版本的SPARC电子结构代码.
- 实施基于Kronecker产品的线性解决器的批量变体,以实现高效的混合功能计算.
- 为了优化NVIDIA GPU架构的代码.
主要方法:
- 开发了一个GPU加速的真实空间SPARC代码.
- 实施了基于Kronecker产品的线性溶解器的批量变体.
- 创建了一个基于数学内核的模块化实现,用于混合函数,将密集操作卸载到GPU上,并将剩余的工作负载转移到CPU上.
主要成果:
- 实现了高达8倍的节点小时加速度和80倍的核心小时,与仅CPU执行相比.
- 将V100 GPU上的6000多个电子的金属系统的溶解时间缩短到大约300秒.
- 在给定的墙时间内显著降低了计算资源需求.
结论:
- 在密度函数理论中,GPU加速为混合函数计算提供了实质性的性能增长.
- 开发的代码可以实现更快,更节省资源的电子结构模拟.
- 这一进步可以促进更大规模的材料建模和发现.
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