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April 10, 2026Journal of Chemical Theory and Computation0 citations

Stochastic GW -GPU: Rapid Quasi-Particle Energies for Molecules beyond 10,000 Atoms

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PTPhillip S. ThomasLawrence Berkeley National LaboratoryMNMinh Tho NguyenUniversity of StuttgartDBDimitri BazileUniversity of California, Los Angeles

Key Points

  • The research aims to enhance the computation of quasi-particle energies using a new GPU-optimized method.
  • Developed Stochastic GW-GPU for improved performance in large-scale systems.
  • Implemented stochastic Resolution of the Identity (sROI) for parallel processing.
  • Executed calculations on hydrogenated silicon clusters with over 10,000 atoms.
  • Achieved individual quasi-particle energies with precision better than ±0.03 eV.
  • Completed computations in under 1 hour.
  • Demonstrated significant performance enhancements compared to previous methods.

Abstract

StochasticGW is a code for computing accurate quasi-particle (QP) energies of molecules and material systems in the GW approximation. StochasticGW utilizes the stochastic Resolution of the Identity (sROI) technique to enable a massively parallel implementation with computational costs that scale semilinearly with system size, allowing the method to access systems with tens of thousands of electrons. We introduce a new implementation, StochasticGW-GPU, for which the main bottleneck steps have been ported to GPUs and give substantial performance improvements over previous versions of the code. We showcase the new code by computing band gaps of hydrogenated silicon clusters (SixHy) containing up to 10,001 atoms and 35,144 electrons, and we obtain individual QP energies with a statistical precision of better than ±0.03 eV with times-to-solution of less than 1 h.

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Cite This Study

Thomas et al. (2026) studied this question.

synapsesocial.com/papers/69d894ec6c1944d70ce05e50https://doi.org/10.1021/acs.jctc.6c00116
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