Graspg – An extension to Grasp2018 based on configuration state function generators

IF 7.2 2区物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Physics Communications Pub Date : 2025-04-04 DOI:10.1016/j.cpc.2025.109604

Ran Si , Yanting Li , Kai Wang , Chongyang Chen , Gediminas Gaigalas , Michel Godefroid , Per Jönsson

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引用次数: 0

Abstract

The Graspg program package is an extension to Grasp2018 (Froese Fischer et al. (2019) [1]) based on configuration state function generators (CSFGs). The generators keep spin-angular integrations at a minimum and reduce substantially the execution time and the memory requirement for large-scale multiconfiguration Dirac-Hartree-Fock (MCDHF) and relativistic configuration interaction (CI) atomic structure calculations. The package includes the improvements reported in Li (2023) [8] in terms of redesigned and efficient constructions of direct and exchange potentials and Lagrange multipliers. In addition, further parallelization of the diagonalization procedure has been implemented. Tools have been developed for predicting configuration state functions (CSFs) that are unimportant and can be discarded for large MCDHF or CI calculations based on results from smaller calculations, thus providing efficient methods for a priori condensation. The package provides a seamless interoperability with Grasp2018. From extensive test runs and benchmarking, we have demonstrated reductions in the execution time and disk file sizes with factors of 37 and 98, respectively, for MCDHF calculations based on large orbital sets compared to corresponding Grasp2018 calculations. For CI calculations, reductions of the execution time with factors over 200 have been attained. With a sensible use of the new possibilities for a priori condensation, CI calculations with nominally hundreds of millions of CSFs can be handled.

PROGRAM SUMMARY

Program Title: Graspg

CPC Library link to program files: https://doi.org/10.17632/7b5kbhy3v9.1

Licensing provisions: MIT License

Programming language: Fortran 95

Nature of problem: Prediction of atomic energy levels using a multiconfiguration Dirac–Hartree–Fock approach.

Solution method: The computational method is the same as in Grasp2018 [1] except that configuration state function generators (CSFGs) have been introduced, a concept that substantially reduces the execution times and memory requirements for large-scale calculations [2]. The method also relies on redesigned and more efficient constructions of direct and exchange potentials and Lagrange multipliers, along with additional parallelization of the diagonalization procedure as detailed in [3].

Additional comments including restrictions and unusual features: 1. provides a seamless interoperability with Grasp2018, 2. options to limit the Breit interaction, 3. includes tools for predicting CSFs that are unimportant and can be discarded for large MCDHF or CI calculations based on the results from smaller calculations.

References

[1]
C. Froese Fischer, G. Gaigalas, P. Jönsson, and J. Bieroń, Comput. Phys. Commun. 237 (2019) 184-187.
[2]
Y. Li, K. Wang, R. Si et al. Comput. Phys. Commun. 283 (2023) 108562.
[3]
Y. Li, J. Li, C. Song et al. Atoms 11 (2023) 12.

查看原文本刊更多论文

Graspg——基于配置状态函数生成器的Grasp2018扩展

Graspg程序包是基于配置状态函数生成器（csfg）的Grasp2018 （Froese Fischer et al.(2019)[1]）的扩展。该生成器将自旋角积分保持在最小，并大大减少了大规模多组态Dirac-Hartree-Fock （MCDHF）和相对论组态相互作用（CI）原子结构计算的执行时间和内存需求。该包包括Li(2023)[8]报告的改进，包括对直接和交换势以及拉格朗日乘数的重新设计和有效构建。此外，还实现了对角化过程的进一步并行化。已经开发了用于预测不重要的配置状态函数（csf）的工具，这些工具可以在基于较小计算结果的大型MCDHF或CI计算中被丢弃，从而为先验冷凝提供了有效的方法。该包提供了与Grasp2018的无缝互操作性。从广泛的测试运行和基准测试中，我们已经证明，与相应的Grasp2018计算相比，基于大轨道集的MCDHF计算的执行时间和磁盘文件大小分别减少了37和98倍。对于CI计算，执行时间减少了200倍以上。通过合理地使用先验凝聚的新可能性，可以处理名义上数以亿计的csf的CI计算。程序摘要程序标题：GraspgCPC库链接到程序文件：https://doi.org/10.17632/7b5kbhy3v9.1Licensing条款：MIT许可证编程语言：Fortran 95问题的性质：使用多配置Dirac-Hartree-Fock方法预测原子能水平。解决方法：计算方法与Grasp2018[1]相同，只是引入了配置状态函数生成器（CSFGs），这一概念大大减少了大规模计算[2]的执行时间和内存需求。该方法还依赖于重新设计和更有效的直接和交换势和拉格朗日乘数的结构，以及对角化过程的额外并行化，详见[3]。附加注释，包括限制和不寻常的功能：提供与grasp2018,2的无缝互操作性。限制英国退欧互动的选项；包括用于预测不重要的csf的工具，这些csf可以在基于较小计算结果的大型MCDHF或CI计算中被丢弃。Froese Fischer， G. Gaigalas， P. Jönsson和J. bieroski, Comput。理论物理。科学通报。237(2019)184-187。李，王锴，司荣等。第一版。理论物理。common . 283 (2023) 108562.[3]李俊杰，宋春林等。原子11 （2023）

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来源期刊

Computer Physics Communications 物理-计算机：跨学科应用

CiteScore

12.10

自引率

3.20%

发文量

287

审稿时长

5.3 months

期刊介绍： The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.