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GPU-Accelerated Large-Scale Excited-State Simulation Based on Divide-and-Conquer Time-Dependent Density-Functional Tight-Binding.

Takeshi YoshikawaNana KomotoYoshifumi NishimuraHiromi Nakai
Published in: Journal of computational chemistry (2019)
The present study implemented the divide-and-conquer time-dependent density-functional tight-binding (DC-TDDFTB) code on a graphical processing unit (GPU). The DC method, which is a linear-scaling scheme, divides a total system into several fragments. By separately solving local equations in individual fragments, the DC method could reduce slow central processing unit (CPU)-GPU memory access, as well as computational cost, and avoid shortfalls of GPU memory. Numerical applications confirmed that the present code on GPU significantly accelerated the TDDFTB calculations, while maintaining accuracy. Furthermore, the DC-TDDFTB simulation of 2-acetylindan-1,3-dione displays excited-state intramolecular proton transfer and provides reasonable absorption and fluorescence energies with the corresponding experimental values. © 2019 Wiley Periodicals, Inc.
Keyphrases
  • dendritic cells
  • blood brain barrier
  • density functional theory
  • working memory
  • molecular dynamics
  • dna binding
  • energy transfer
  • molecular dynamics simulations
  • virtual reality
  • binding protein
  • transcription factor