DFT-FE 1.0: A massively parallel hybrid CPU-GPU density functional theory code using finite-element discretization

Das, Sambit; Motamarri, Phani; Subramanian, Vishal; Rogers, David M.; Gavini, Vikram

doi:10.1016/j.cpc.2022.108473

Title: DFT-FE 1.0: A massively parallel hybrid CPU-GPU density functional theory code using finite-element discretization

Journal Article · 03 August 2022 · Computer Physics Communications

DOI: https://doi.org/10.1016/j.cpc.2022.108473 · OSTI ID:1888932

Das, Sambit ^[1]; Motamarri, Phani ^[2]; Subramanian, Vishal ^[1];

^[3];

^[1]

Univ. of Michigan, Ann Arbor, MI (United States)
Indian Inst. of Science, Bangalore (India)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

In this work, we present DFT-FE 1.0, building on DFT-FE 0.6 [Comput. Phys. Commun. 246, 106853 (2020)], to conduct fast and accurate large-scale density functional theory (DFT) calculations (reaching ~ 100,000 electrons) on both many-core CPU and hybrid CPU-GPU computing architectures. This work involves improvements in the real-space formulation—via an improved treatment of the electrostatic interactions that substantially enhances the computational efficiency—as well high-performance computing aspects, including the GPU acceleration of all the key compute kernels in DFT-FE. We demonstrate the accuracy by comparing the ground-state energies, ionic forces and cell stresses on a wide-range of benchmark systems against those obtained from widely used DFT codes. Further, we demonstrate the numerical efficiency of our implementation, which yields ~ 20× CPU-GPU speed-up by using GPU acceleration on hybrid CPU-GPU nodes. Notably, owing to the parallel-scaling of the GPU implementation, we obtain wall-times of 80–140 seconds for full ground-state calculations, with stringent accuracy, on benchmark systems containing ~ 6, 000 – 15,000 electrons.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF); US Air Force Office of Scientific Research (AFOSR); US Army Research Office (ARO)

Grant/Contract Number:: AC05-00OR22725; SC0008637; AC02-05CH11231

OSTI ID:: 1888932

Journal Information:: Computer Physics Communications, Journal Name: Computer Physics Communications Journal Issue: 1 Vol. 280; ISSN 0010-4655

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Title: DFT-FE 1.0: A massively parallel hybrid CPU-GPU density functional theory code using finite-element discretization

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