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Accelerating Coupled-Cluster Calculations with GPUs: An Implementation of the Density-Fitted CCSD(T) Approach for

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This study presents a new algorithm for coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] calculations using graphics processing units (GPUs). The hybrid CPU-GPU approach significantly accelerates computational chemistry, enabling larger molecular simulations.

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Area of Science:

  • Computational Chemistry
  • High-Performance Computing
  • Quantum Chemistry

Background:

  • Coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] is a high-accuracy quantum chemistry method.
  • Large-scale CCSD(T) calculations are computationally demanding, limiting their application to smaller systems.
  • Heterogeneous computing platforms offer potential for accelerating these calculations.

Purpose of the Study:

  • To develop and implement an efficient algorithm for RI-CCSD(T) calculations on hybrid CPU-GPU architectures.
  • To leverage OpenMP directives for GPU offloading of computationally intensive terms.
  • To demonstrate the performance and scalability of the developed code on pre-exascale and exascale supercomputers.

Main Methods:

  • Algorithm development for resolution-of-the-identity (RI) approximation in CCSD(T).
  • GPU offloading of RI-CCSD amplitude equations and perturbative triples correction using OpenMP.
  • Utilization of accelerated math libraries (cuBLAS/hipBLAS) for tensor contractions.
  • Strategies for data tiling and minimizing CPU-GPU data transfer.

Main Results:

  • Achieved speedups of 4-8× for GPU-offloaded RI-CCSD terms compared to CPU-only implementations.
  • Demonstrated increasing acceleration for perturbative triples correction with molecule size, reaching 5.7× for C66H20.
  • Enabled computation of RI-CCSD(T) for C60 in 7 minutes on the Frontier exascale supercomputer using 12,288 AMD GPUs with 83.1% parallel efficiency.

Conclusions:

  • The hybrid CPU-GPU RI-CCSD(T) algorithm provides significant computational acceleration.
  • The approach enables accurate quantum chemical calculations for larger molecular systems.
  • This work paves the way for routine high-accuracy electronic structure calculations on modern supercomputing architectures.