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Noniterative Multireference Coupled Cluster Methods on Heterogeneous CPU-GPU Systems.

Kiran Bhaskaran-Nair1, Wenjing Ma1, Sriram Krishnamoorthy1

  • 1William R. Wiley Environmental Molecular Sciences Laboratory, Battelle, Pacific Northwest National Laboratory, K8-91, P.O. Box 999, Richland, Washington 99352, United States.

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Summary
This summary is machine-generated.

This study introduces a novel parallel algorithm combining reference-level parallelism (RLP) and graphics processing units (GPUs) to accelerate noniterative multireference coupled cluster (MRCC) theories, enhancing computational efficiency for complex quantum chemistry calculations.

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Area of Science:

  • Quantum Chemistry
  • Computational Physics
  • High-Performance Computing

Background:

  • Multireference coupled cluster (MRCC) theories are crucial for describing complex electronic structures.
  • Existing methods face computational challenges due to their high complexity.
  • Accelerating these calculations is essential for advancing chemical accuracy.

Purpose of the Study:

  • To present a novel parallel algorithm for noniterative MRCC theories.
  • To merge reference-level parallelism (RLP) with graphics processing unit (GPU) acceleration.
  • To enhance the computational efficiency of complex quantum chemical calculations.

Main Methods:

  • Developed a parallel algorithm integrating RLP and GPU acceleration.
  • Applied the algorithm to the MRCCSD(T) method, incorporating perturbative triples.
  • Utilized Brillouin-Wigner (BW) and Mukherjee (Mk) state-specific MRCCSD(T) formulations for performance illustration.

Main Results:

  • Demonstrated the successful implementation of the combined RLP/GPU algorithm.
  • Showcased performance improvements for noniterative MRCC calculations.
  • Validated the approach on specific MRCCSD(T) formulations.

Conclusions:

  • The combined RLP/GPU algorithm offers a significant speedup for noniterative MRCC theories.
  • This approach enhances the feasibility of applying advanced quantum chemical methods.
  • The developed algorithm represents a step forward in computational quantum chemistry.