Abstract
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. 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.
| Original language | English |
|---|---|
| Article number | 084802 |
| Journal | Journal of Chemical Physics |
| Volume | 158 |
| Issue number | 8 |
| DOIs | |
| State | Published - Feb 28 2023 |
Funding
We appreciate valuable comments and suggestions from Jack Wells. We gratefully acknowledge support for this work on OLCF Summit through the Directors Discretionary Allocation CHM152 (2018–2020). C.C. and C.C. acknowledge financial support from the Rectory and the Vice-rectory for research of the University of Costa Rica through Grant No. 115-B9-461. V.-Q.V. acknowledges support by an Energy Science and Engineering Fellowship of the Bredesen Center for Interdisciplinary Research and Graduate Education at the University of Tennessee, Knoxville. S.I. acknowledges support from the Fluid Interface Reactions, Structures, and Transport (FIRST) Center, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.