DFT-FE - A massively parallel adaptive finite-element code for large-scale density functional theory calculations. We present an accurate, efficient and massively parallel finite-element code, DFT-FE, for large-scale ab-initio calculations (reaching 100,000 electrons) using Kohn–Sham density functional theory (DFT). DFT-FE is based on a local real-space variational formulation of the Kohn–Sham DFT energy functional that is discretized using a higher-order adaptive spectral finite-element (FE) basis, and treats pseudopotential and all-electron calculations in the same framework, while accommodating non-periodic, semi-periodic and periodic boundary conditions. We discuss the main aspects of the code, which include, the various strategies of adaptive FE basis generation, and the different approaches employed in the numerical implementation of the solution of the discrete Kohn–Sham problem that are focused on significantly reducing the floating point operations, communication costs and latency. We demonstrate the accuracy of DFT-FE by comparing the energies, ionic forces and periodic cell stresses on a wide range of problems with popularly used DFT codes. Further, we demonstrate that DFT-FE significantly outperforms widely used plane-wave codes—both in CPU-times and wall-times, and on both non-periodic and periodic systems—at systems sizes beyond a few thousand electrons, with over fold speedups in systems with more than 10,000 electrons. The benchmark studies also highlight the excellent parallel scalability of DFT-FE, with strong scaling demonstrated up to 192,000 MPI tasks.
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References in zbMATH (referenced in 2 articles )
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- Arndt, Daniel; Bangerth, Wolfgang; Davydov, Denis; Heister, Timo; Heltai, Luca; Kronbichler, Martin; Maier, Matthias; Pelteret, Jean-Paul; Turcksin, Bruno; Wells, David: The \textscdeal.II finite element library: design, features, and insights (2021)
- Temizer, İ.; Motamarri, P.; Gavini, V.: NURBS-based non-periodic finite element framework for Kohn-Sham density functional theory calculations (2020)