在ORCA中生成代码:进步,效率和紧密的集成
Marvin H Lechner1, Anastasios Papadopoulos1, Kantharuban Sivalingam1
1Department of Molecular Theory and Spectroscopy, Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr, Germany. frank.neese@kofo.mpg.de.
Physical chemistry chemical physics : PCCP
|May 20, 2024
概括
自动代码生成器ORCA-AGE II现在使用C++显著提高性能,并处理复杂的理论,如fic-MRCC. 这通过自动化代码生成和减少开发时间来增强计算化学研究.
科学领域:
- 计算化学的计算化学
- 量子化学 是一个量子化学.
- 软件开发 软件开发
背景情况:
- ORCA-AGE (自动生成环境) 工具链以前使用Python来生成计算化学代码.
- 开发复杂的量子化学理论需要大量的编程时间和精力.
研究的目的:
- 为了介绍ORCA-AGE II,这是自动代码生成器的显著改进版本.
- 为了提高性能,模块化和与ORCA量子化学软件的集成.
- 为了实现高度复杂的理论方法和自动化梯度计算.
主要方法:
- 在C++中重写ORCA-AGE工具链以优化性能.
- 实施模块化设计以更容易地集成复杂的代码引擎.
- 实现与ORCA主机程序紧密集成,用于自动代码生成和编译.
- 开发用于生成平行生产级代码的能力,用于像fic-MRCC这样的先进理论.
主要成果:
- 与Python版本相比,实现了高达两个数量级的性能增长.
- 能够为高度复杂的理论生成并行代码,包括完全内部合约的多引用合集群 (fic-MRCC) 理论.
- 证明了对任意理论的核梯度的自动实现.
- 通过自动生成和集成,确保长寿和统一的代码质量.
结论:
- ORCA-AGE II显著加速了先进的计算化学方法的开发和实施.
- 该工具使研究人员能够专注于理论开发,而不是实施细节.
- 这种进步有助于研究以前过于复杂而无法实际实施的理论.
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