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现代异构超级计算机上的耦合簇理论

Coupled cluster theory on modern heterogeneous supercomputers.

作者信息

Corzo Hector H, Hillers-Bendtsen Andreas Erbs, Barnes Ashleigh, Zamani Abdulrahman Y, Pawłowski Filip, Olsen Jeppe, Jørgensen Poul, Mikkelsen Kurt V, Bykov Dmytro

机构信息

Oak Ridge National Laboratory, Oak Ridge, TN, United States.

Department of Chemistry, University of Copenhagen, Copenhagen, Denmark.

出版信息

Front Chem. 2023 Jun 14;11:1154526. doi: 10.3389/fchem.2023.1154526. eCollection 2023.

Abstract

This study examines the computational challenges in elucidating intricate chemical systems, particularly through methodologies. This work highlights the Divide-Expand-Consolidate (DEC) approach for coupled cluster (CC) theory-a linear-scaling, massively parallel framework-as a viable solution. Detailed scrutiny of the DEC framework reveals its extensive applicability for large chemical systems, yet it also acknowledges inherent limitations. To mitigate these constraints, the cluster perturbation theory is presented as an effective remedy. Attention is then directed towards the CPS (D-3) model, explicitly derived from a CC singles parent and a doubles auxiliary excitation space, for computing excitation energies. The reviewed new algorithms for the CPS (D-3) method efficiently capitalize on multiple nodes and graphical processing units, expediting heavy tensor contractions. As a result, CPS (D-3) emerges as a scalable, rapid, and precise solution for computing molecular properties in large molecular systems, marking it an efficient contender to conventional CC models.

摘要

本研究探讨了在阐明复杂化学系统时所面临的计算挑战,特别是通过相关方法。这项工作强调了用于耦合簇(CC)理论的“分割-扩展-整合”(DEC)方法——一种线性缩放、大规模并行框架——是一种可行的解决方案。对DEC框架的详细审查揭示了其在大型化学系统中的广泛适用性,但也承认其存在固有局限性。为了减轻这些限制,提出了簇微扰理论作为一种有效的补救措施。然后将注意力转向CPS(D-3)模型,该模型明确地从CC单激发母空间和双激发辅助空间导出,用于计算激发能。所审查的CPS(D-3)方法的新算法有效地利用了多个节点和图形处理单元,加速了繁重的张量收缩。结果,CPS(D-3)成为在大型分子系统中计算分子性质的一种可扩展、快速且精确的解决方案,使其成为传统CC模型的一个有力竞争者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/10303140/a76803b745a5/fchem-11-1154526-g001.jpg

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