Acceleration of the density-functional tight-binding (DFTB) method on single and multiple graphical processing units (GPUs) was accomplished using the MAGMA linear algebra library. Herein two major computational bottlenecks of DFTB ground-state calculations were addressed in our implementation: the Hamiltonian matrix diagonalization and the density matrix construction. The code was implemented and benchmarked on two different computer systems: (1) the SUMMIT IBM Power9 supercomputer at the Oak Ridge National Laboratory Leadership Computing Facility with 1–6 NVIDIA Volta V100 GPUs per computer node and (2) an in-house Intel Xeon computer with 1–2 NVIDIA Tesla P100 GPUs. The performance and parallel scalability were measured for three molecular models of 1-, 2-, and 3-dimensional chemical systems, represented by carbon nanotubes, covalent organic frameworks, and water clusters.
Vuong, Van-Quan, et al. "Accelerating the density-functional tight-binding method using graphical processing units." Journal of Chemical Physics, vol. 158, no. 8, Feb. 2023. https://doi.org/10.1063/5.0130797
@article{osti_1959613,
author = {Vuong, Van-Quan and Cevallos, Caterina and Hourahine, Ben and Aradi, Bálint and Jakowski, Jacek and Irle, Stephan and Camacho, Cristopher},
title = {Accelerating the density-functional tight-binding method using graphical processing units},
annote = {Acceleration of the density-functional tight-binding (DFTB) method on single and multiple graphical processing units (GPUs) was accomplished using the MAGMA linear algebra library. Herein two major computational bottlenecks of DFTB ground-state calculations were addressed in our implementation: the Hamiltonian matrix diagonalization and the density matrix construction. The code was implemented and benchmarked on two different computer systems: (1) the SUMMIT IBM Power9 supercomputer at the Oak Ridge National Laboratory Leadership Computing Facility with 1–6 NVIDIA Volta V100 GPUs per computer node and (2) an in-house Intel Xeon computer with 1–2 NVIDIA Tesla P100 GPUs. The performance and parallel scalability were measured for three molecular models of 1-, 2-, and 3-dimensional chemical systems, represented by carbon nanotubes, covalent organic frameworks, and water clusters.},
doi = {10.1063/5.0130797},
url = {https://www.osti.gov/biblio/1959613},
journal = {Journal of Chemical Physics},
issn = {ISSN 0021-9606},
number = {8},
volume = {158},
place = {United States},
publisher = {American Institute of Physics (AIP)},
year = {2023},
month = {02}}
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Energy Frontier Research Centers (EFRC) (United States). Fluid Interface Reactions, Structures, and TRANSPORT (FIRST)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES); University of Costa Rica
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1959613
Alternate ID(s):
OSTI ID: 1958630
Journal Information:
Journal of Chemical Physics, Journal Name: Journal of Chemical Physics Journal Issue: 8 Vol. 158; ISSN 0021-9606
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 372, Issue 2011https://doi.org/10.1098/rsta.2012.0483