Metascalable Quantum Molecular Dynamics Simulations of Hydrogen-on-Demand

摘要

We enabled an unprecedented scale of quantum molecular dynamics simulations through algorithmic innovations. A new lean divide-and-conquer density functional theory algorithm significantly reduces the prefactor of the O(N) computational cost based on complexity and error analyses. A globally scalable and locally fast solver hybridizes a global real-space multigrid with local plane-wave bases. The resulting weak-scaling parallel efficiency was 0.984 on 786,432 IBM Blue Gene/Q cores for a 50.3 million-atom (39.8 trillion degrees-of-freedom) system. The time-to-solution was 60-times less than the previous state-of-the art, owing to enhanced strong scaling by hierarchical band-space domain decomposition and high floating-point performance (50.5% of the peak). Production simulation involving 16,661 atoms for 21,140 time steps (or 129,208 self-consistent-field iterations) revealed a novel nanostructural design for on-demand hydrogen production from water, advancing renewable energy technologies. This metascalable (or "design once, scale on new architectures") algorithm is used for broader applications within a recently proposed divide-conquer-recombine paradigm.