一个模块化,复合框架,用于利用缩小规模的库伦和交换构建算法:设计和实施
David Poole1, David B Williams-Young2, Andy Jiang1
1Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA.
在Psi4中,一个新的CompositeJK框架集成了用于计算Fock矩阵元素的各种算法. 这使得显著的性能改进,特别是图形处理单元 (GPU) 加速用于量子化学计算.
科学领域:
- 量子化学 是一个量子化学.
- 计算化学计算化学
- 材料科学 材料科学 材料科学
背景情况:
- 存在多个算法来计算库伦 (J) 和交换 (K) 对Fock-like矩阵的贡献.
- 将多种J和K构建算法集成到统一的框架中,有利于计算效率.
研究的目的:
- 实施一个灵活的框架",CompositeJK",用于在量子化学中组合不同的J和K构建算法.
- 通过整合新的计算方法和硬件加速来增强Psi4的能力.
主要方法:
- 在Psi4量子化学软件中实现"复合JK"形式主义.
- 将Psi4与来自GauXC库的sn-LinK实现连接起来.
- 利用中央处理单元 (CPU) 和图形处理单元 (GPU) 来构建福克矩阵元件.
主要成果:
- 复合JK框架允许J和K算法的模块化组合用于各种量子化学方法.
- 与sn-LinK的集成提供了第一个非商业GPU支持Psi4.4中的Fock矩阵构造.
- 基于CPU的sn-LinK显示了对大型系统的现有Psi4JK方法的2.8倍速度.
- 通过GPU加速的sn-LinK实现了高达7.0倍的性能增长.
结论:
- 复合JK框架为开发和利用量子化学中先进的计算方法提供了直观和模块化的方法.
- 集成sn-LinK,特别是与GPU加速,显著提高了在Psi4中的Fock矩阵计算的性能.
- 这一进步促进了更大,更复杂的量子化学模拟,使材料科学等领域受益.
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