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Metascalable Quantum Molecular Dynamics Simulations of Hydrogen-on-Demand

  • Ken Ichi Nomura
  • , Rajiv K. Kalia
  • , Aiichiro Nakano
  • , Priya Vashishta
  • , Kohei Shimamura
  • , Fuyuki Shimojo
  • , Manaschai Kunaseth
  • , Paul C. Messina
  • , Nichols A. Romerod

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

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.
Original languageEnglish
Title of host publicationInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC
Pages661-673
Number of pages13
Volume2015-January
EditionJanuary
DOIs
StatePublished - Jan 16 2014
Externally publishedYes

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