Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures

Johann V. Pototschnig*, Anastasios Papadopoulos, Dmitry I. Lyakh, Michal Repisky, Loïc Halbert, André Severo Pereira Gomes, Hans Jørgen Aa Jensen, Lucas Visscher

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


In this paper, we report reimplementation of the core algorithms of relativistic coupled cluster theory aimed at modern heterogeneous high-performance computational infrastructures. The code is designed for parallel execution on many compute nodes with optional GPU coprocessing, accomplished via the new ExaTENSOR back end. The resulting ExaCorr module is primarily intended for calculations of molecules with one or more heavy elements, as relativistic effects on the electronic structure are included from the outset. In the current work, we thereby focus on exact two-component methods and demonstrate the accuracy and performance of the software. The module can be used as a stand-alone program requiring a set of molecular orbital coefficients as the starting point, but it is also interfaced to the DIRAC program that can be used to generate these. We therefore also briefly discuss an improvement of the parallel computing aspects of the relativistic self-consistent field algorithm of the DIRAC program.

Original languageEnglish
Pages (from-to)5509-5529
Number of pages21
JournalJournal of chemical theory and computation
Issue number9
Early online date9 Aug 2021
Publication statusPublished - 14 Sept 2021

Bibliographical note

Funding Information:
This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. Some computer codes used in this research (ExaTENSOR, TAL-SH, partly ExaCorr) were developed during the OLCF-4 Center for Accelerated Application Readiness (CAAR) program funded by the US Department of Energy at the Oak Ridge National Laboratory. ASPG and LH acknowledge support from PIA ANR project CaPPA (ANR-11-LABX-0005-01), the Franco-German project CompRIXS (Agence nationale de la recherche ANR-19-CE29-0019, Deutsche Forschungsgemeinschaft JA 2329/6-1), the I-SITE ULNE project OVERSEE, the French Ministry of Higher Education and Research, region Hauts de France council, the European Regional Development Fund (ERDF) project CPER CLIMIBIO, and the French national supercomputing facilities (grants DARI A0070801859 and Joliot Curie grands challenges 2019 gch0417). ASPG, LH, JVP, and LV acknowledge support from MESONM International Associated Laboratory (LAI) (ANR-16-IDEX-0004). J.V.P. acknowledges funding from the Austrian Science Fund (FWF, J 4177-N36). M.R. acknowledges the funding support from the Research Council of Norway through a Center of Excellence Grant (Grant no. 262695).

Publisher Copyright:
© 2021 The Authors. Published by American Chemical Society

Copyright 2021 Elsevier B.V., All rights reserved.


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