research-article

Metascalable quantum molecular dynamics simulations of hydrogen-on-demand

Authors:

Ken-ichi Nomura,

Rajiv K. Kalia,

Aiichiro Nakano,

Priya Vashishta,

Kohei Shimamura,

Fuyuki Shimojo,

Manaschai Kunaseth,

Paul C. Messina,

Nichols A. RomeroAuthors Info & Claims

SC '14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

Pages 661 - 673

https://doi.org/10.1109/SC.2014.59

Published: 16 November 2014 Publication History

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-spacedomain 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.

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Cited By

Tiwari SKrishnamoorthy ARajak PSakdhnagool PKunaseth MShimojo FFukushima SNakano ALuo YKalia RNomura KVashishta P(2020)Quantum Dynamics at ScaleProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3368474.3368489(1-10)Online publication date: 15-Jan-2020
https://dl.acm.org/doi/10.1145/3368474.3368489
Small PLiu KTiwari SKalia RNakano ANomura KVashishta P(2018)Acceleration of Dynamic n-Tuple Computations in Many-Body Molecular DynamicsProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3149457.3149463(159-170)Online publication date: 28-Jan-2018
https://dl.acm.org/doi/10.1145/3149457.3149463
Cheng HRajak PSheng CKalia RNakano AVashishta PWeinbub JBaboulin MThacker WPolok L(2016)A high-throughput multiobjective genetic-algorithm workflow for in situ training of reactive molecular-dynamics force fieldsProceedings of the 24th High Performance Computing Symposium10.22360/SpringSim.2016.HPC.004(1-6)Online publication date: 3-Apr-2016
https://dl.acm.org/doi/10.22360/SpringSim.2016.HPC.004
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Index Terms

Metascalable quantum molecular dynamics simulations of hydrogen-on-demand
1. Applied computing
  1. Physical sciences and engineering
    1. Chemistry
    2. Physics

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SC '14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

November 2014

1054 pages

ISBN:9781479955008

General Chair:
Trish Damkroger
Lawrence Livermore National Laboratory, Livermore, California
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Jack Dongarra
University of Tennessee, Knoxville, Tennessee

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Published: 16 November 2014

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SC '14: International Conference for High Performance Computing, Networking, Storage and Analysis

November 16 - 21, 2014

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Cited By

Tiwari SKrishnamoorthy ARajak PSakdhnagool PKunaseth MShimojo FFukushima SNakano ALuo YKalia RNomura KVashishta P(2020)Quantum Dynamics at ScaleProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3368474.3368489(1-10)Online publication date: 15-Jan-2020
https://dl.acm.org/doi/10.1145/3368474.3368489
Small PLiu KTiwari SKalia RNakano ANomura KVashishta P(2018)Acceleration of Dynamic n-Tuple Computations in Many-Body Molecular DynamicsProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3149457.3149463(159-170)Online publication date: 28-Jan-2018
https://dl.acm.org/doi/10.1145/3149457.3149463
Cheng HRajak PSheng CKalia RNakano AVashishta PWeinbub JBaboulin MThacker WPolok L(2016)A high-throughput multiobjective genetic-algorithm workflow for in situ training of reactive molecular-dynamics force fieldsProceedings of the 24th High Performance Computing Symposium10.22360/SpringSim.2016.HPC.004(1-6)Online publication date: 3-Apr-2016
https://dl.acm.org/doi/10.22360/SpringSim.2016.HPC.004
Nakano AHattori SKalia RMou WNomura KRajak PVashishta PShimamura KShimojo FKunaseth MOhmura SMessina PRomero N(2014)Divide-Conquer-RecombineProceedings of the 20 Years of Beowulf Workshop on Honor of Thomas Sterling's 65th Birthday10.1145/2737909.2737911(17-27)Online publication date: 13-Oct-2014
https://dl.acm.org/doi/10.1145/2737909.2737911

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