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We reimplemented relativistic coupled cluster theory algorithms for modern high-performance computing, enhancing calculations for molecules with heavy elements using the ExaCorr module and GPU acceleration.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • High-Performance Computing

Background:

  • Relativistic effects are crucial for accurate electronic structure calculations of heavy elements.
  • Existing computational methods may not fully leverage modern heterogeneous computing architectures.
  • Efficient implementation of relativistic quantum chemistry methods is essential for scientific discovery.

Purpose of the Study:

  • To report the reimplementation of relativistic coupled cluster theory algorithms.
  • To optimize these algorithms for modern heterogeneous high-performance computational infrastructures, including GPU coprocessing.
  • To develop the ExaCorr module for accurate and efficient calculations of molecules with heavy elements.

Main Methods:

  • Reimplementation of core relativistic coupled cluster algorithms.
  • Development of the ExaCorr module utilizing the ExaTENSOR back end for parallel execution and GPU acceleration.
  • Focus on exact two-component methods for relativistic electronic structure calculations.
  • Interfacing ExaCorr with the DIRAC program for generating molecular orbital coefficients.

Main Results:

  • The ExaCorr module is designed for parallel execution on many compute nodes with optional GPU coprocessing.
  • The software demonstrates accuracy and performance for relativistic electronic structure calculations.
  • The module can be used as a stand-alone program or interfaced with the DIRAC program.
  • Improvements to the parallel computing aspects of the DIRAC program's relativistic self-consistent field algorithm are discussed.

Conclusions:

  • The ExaCorr module provides an efficient and accurate computational tool for studying molecules with heavy elements.
  • The reimplementation effectively utilizes modern high-performance computing resources, including GPUs.
  • The integration with DIRAC enhances the workflow for relativistic quantum chemistry calculations.