A massively parallel domain decomposition method for large-scale DFT electronic structure calculations

Abstract

We present a massively parallel domain decomposition method for atoms and grids to enable large-scale density functional theory (DFT) electronic structure calculations. In the atom decomposition, we develop a modified recursive bisection method based on the moment of inertia tensor for reordering the atoms from 3D to 1D along a principal axis so that atoms that are close in real space are also close on the axis to ensure data locality. The atoms are then divided into sub-domains depending on their projections onto the principal axis in a balanced way among the processes. In the grid decomposition, we define four data structures to make data locality consistent with that of the clustered atoms, and propose a 2D decomposition method for solving the Poisson equation using the 3D FFT with communication volume minimized. Benchmark results show that the parallel efficiency at 131,072 cores is 67.7\% compared to the baseline of 16,384 cores on the K computer.