在使用CRYSTAL的CPU/GPU架构上进行大型DFT材料计算的加速线性代数
Giacomo Ambrogio1, Lorenzo Donà1, Jacques K Desmarais1
1Dipartimento di Chimica, Università di Torino, via Giuria 5, 10125 Torino, Italy.
The Journal of chemical physics
|February 25, 2025
概括
图形处理单元 (GPU) 为水晶电子结构包加速线性代数,显著降低大型系统上固态密度函数理论模拟的计算成本.
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:
- 固态密度函数理论 (DFT) 模拟需要大量的计算资源.
- 加快线性代数运算对于提高DFT性能至关重要.
- 晶体电子结构包被广泛用于固态DFT计算.
研究的目的:
- 在Crystal包的自相一致的字段驱动器中实现和评估线性代数运算的图形处理单元 (GPU) 加速.
- 评估多个设备和系统大小的GPU加速的性能扩展.
- 将GPU加速方法的效率与传统的仅使用中央处理器 (CPU) 的策略进行比较.
主要方法:
- 矩阵乘法,对角化,反转和Cholesky分解的GPU加速.
- 在各种系统上进行测试:α-石英,ZIF-8和生物MOF.
- 研究与系统大小 (高达2808个原子) 和GPU数量 (1-8个节点) 的扩展.
- 通过通用梯度近似 (GGA) 和混合GGA函数来评估性能.
主要成果:
- 在多个设备上,GPU加速的显著规律缩放.
- 与仅使用CPU的方法相比,大系统的计算成本大幅降低.
- 单个GPU性能相当于512-1024个CPU核心,用于大型生物MOF系统上的特定任务.
结论:
- GPU 加速为水晶 DFT 模拟提供了相当大的加速度.
- 实施的战略使得以前难以处理的大型系统的有效计算成为可能.
- 这一进步显著降低了固态DFT研究的计算障碍.
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