Building the Bridge to Exascale: Applications and Opportunities in Materials, Chemistry, and Biology I

Presentations

• Towards a Realistic Description of H₃O+ and OH- Transport through Confined Environments using Machine Learning and an Order-N Framework for Condensed-Phase Hybrid Density Functional Theory

  ORAL · Invited

  March 14, 2022, 11:30 AM – March 14, 2022, 12:06 PM

  Presenters

  • Robert A Distasio

    • Cornell University

  Authors

  • Robert A Distasio

    • Cornell University

  View abstract →

• Fueling a Data-Driven Machine Learning Model for H₃O⁺ and OH^- Transport through Confined Aqueous Environments: A High-Throughput Order-N Framework for Condensed-Phase Hybrid Density Functional Theory at Work

  ORAL

  March 14, 2022, 12:06 PM – March 14, 2022, 12:18 PM

  Presenters

  • Hsin-Yu Ko

    • Cornell University

  Authors

  • Hsin-Yu Ko

    • Cornell University

  • Marcos F Calegari Andrade

    • Princeton University

  • Zachary M Sparrow

    • Cornell University

  • Brian G Ernst

    • Cornell University

  • Jalen A Harris

    • Cornell University

  • Robert A Distasio

    • Cornell University

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• Optimization and performance of RMG DFT-based electronic structure software on exascale architectures

  ORAL

  March 14, 2022, 12:18 PM – March 14, 2022, 12:30 PM

  Presenters

  • Emil Briggs

    • North Carolina State University

  Authors

  • Emil Briggs

    • North Carolina State University

  • Wenchang Lu

    • North Carolina State University

  • Jerry Bernholc

    • North Carolina State University

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• CPU-GPU optimization and performance of RMG linear-scaling module with optimally localized orbitals

  ORAL

  March 14, 2022, 12:30 PM – March 14, 2022, 12:42 PM

  Presenters

  • Wenchang Lu

    • North Carolina State University

  Authors

  • Wenchang Lu

    • North Carolina State University

  • Emil Briggs

    • North Carolina State University

  • Jerry Bernholc

    • North Carolina State University

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• Large-Scale Materials Science Codes Porting Strategies for Next Generation Exascale Architectures

  ORAL

  March 14, 2022, 12:42 PM – March 14, 2022, 12:54 PM

  Presenters

  • Mauro Del Ben

    • Lawrence Berkeley National Laboratory

  Authors

  • Mauro Del Ben

    • Lawrence Berkeley National Laboratory

  • Steven G Louie

    • University of California at Berkeley, and Lawrence Berkeley National Laboratory
    • Physics Department, UC Berkeley and Lawrence Berkeley National Lab
    • University of California Berkeley
    • University of California, Berkeley
    • University of California at Berkeley; Lawrence Berkeley National Laboratory
    • University of California at Berkeley and Lawrence Berkeley National Laboratory
    • UC berkeley
    • University of California at Berkeley and Lawrence Berkeley National Lab
    • UC Berkeley & Lawrence Berkeley National Laboratory

  • Jack R Deslippe

    • Lawrence Berkeley National Laboratory
    • LBNL

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• GPU-Acceleration of Large-Scale Full-Frequency GW Calculations

  ORAL

  March 14, 2022, 12:54 PM – March 14, 2022, 1:06 PM

  Presenters

  • Victor Yu

    • Argonne National Laboratory

  Authors

  • Victor Yu

    • Argonne National Laboratory

  • Marco Govoni

    • Argonne National Laboratory

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• QMCPACK performance portability on NVIDIA and AMD GPUs

  ORAL

  March 14, 2022, 1:06 PM – March 14, 2022, 1:18 PM

  Presenters

  • Ye Luo

    • Argonne National Laboratory

  Authors

  • Ye Luo

    • Argonne National Laboratory

  • Peter Doak

    • Oak Ridge National Laboratory

  • Paul Kent

    • Oak Ridge National Lab
    • Oak Ridge National Laboratory

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• Using high accuracy many-body methods (QMC and sCI) to describe ground state and excited state properties of strongly correlated battery cathodes

  ORAL

  March 14, 2022, 1:18 PM – March 14, 2022, 1:30 PM

  Presenters

  • Anouar Benali

    • Computational Science Division, Argonne National Laboratory
    • Computational Science Division, Argonne National Laboratory, Argonne, IL, United States
    • Argonne National Labratory
    • Argonne National Laboratory

  Authors

  • Anouar Benali

    • Computational Science Division, Argonne National Laboratory
    • Computational Science Division, Argonne National Laboratory, Argonne, IL, United States
    • Argonne National Labratory
    • Argonne National Laboratory

  • kevin E gasperich

    • Argonne National Laboratory

  • Tomas Rojas

    • Department of Chemical Engineering, University of Illinois at Chicago, Chicago, Illinois 60608, United States
    • Argonne National Laboratory

  • Vijay R Singh

    • Department of Chemical Engineering, University of Illinois at Chicago, Chicago, Illinois 60608, United States, Materials Science Division, ANL, Argonne, IL, USA
    • Department of Physics, University of Illinois at Chicago, Chicago, IL, 60607
    • Univ Illinois at Chicago & MSD, ANL
    • University of Illinois at Chicago
    • Chemical Engineering Department, University of Illinois at Chicago
    • Department of Chemical Engineering, University of Illinois at Chicago, Chicago, Illinois 60608, United States, Materials Science Division, Argonne National Laboratory, IL, USA

  • Pallab Barai

    • Argonen National Laboratory

  • Anh T Ngo

    • Department of Chemical Engineering, University of Illinois at Chicago, Chicago, Illinois 60608, United States, Materials Science Division, ANL, Argonne, IL, USA
    • Department of Chemical Engineering, University of Illinois at Chicago, Chicago, Illinois 60608, United States, Materials Science Division, Argonne National Laboratory, IL, USA
    • University of Illinois in Chicago

  • Hyeondeok Shin

    • Argonne National Laboratory

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• Forces, stresses and related properties in solids by plane-wave auxiliary-field quantum Monte Carlo

  ORAL

  March 14, 2022, 1:30 PM – March 14, 2022, 1:42 PM

  Publication: [1] S. Zhang and H. Krakauer, Phys. Rev. Lett. 90, 136401 (2003); M. Suewattana, W. Purwanto, S. Zhang, H. Krakauer, and E. J. Walter, Phys. Rev. B 75, 245123 (2007)
  [2] S. Zhang, J. Carlson, and J.E. Gubernatis, Phys. Rev. B 55, 7464 (1997); M. Motta and S. Zhang, J. Chem. Theory Comput. 13, 5367 (2017)
  [3] S. Chen, M. Motta, F. Ma, and S. Zhang, Phys. Rev. B 103, 075138 (2021)
  [4] J. Shee, S. Zhang, D.R. Reichman, and R.A. Friesner, J. Chem. Theory Comput. 13, 6, 2667 (2017)

  Presenters

  • Siyuan Chen

    • William & Mary

  Authors

  • Siyuan Chen

    • William & Mary

  • Fengjie Ma

    • Beijing Normal University

  • Shiwei Zhang

    • Simons Foundation

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• Ab initio Calculations in Atoms, Molecules, and Solids, Treating Spin-Orbit Coupling and Electron Interaction on Equal Footing

  ORAL

  March 14, 2022, 1:42 PM – March 14, 2022, 1:54 PM

  Publication: Brandon Eskridge, Henry Krakauer, Hao Shi, and Shiwei Zhang. Ab initio Calculations in Atoms, Molecules, and Solids, Treating Spin-Orbit Coupling and Electron Interaction on Equal Footing. arXiv:2110.10201

  Presenters

  • Brandon Eskridge

    • William & Mary

  Authors

  • Brandon Eskridge

    • William & Mary

  • Henry Krakauer

    • William & Mary

  • Hao Shi

    • Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, USA
    • University of Delaware

  • Shiwei Zhang

    • Simons foundation
    • Simons Foundation
    • Flatiron Institute

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• Electronic structure calculations at finite temperature using the piecewise interaction picture density matrix quantum Monte Carlo approach

  ORAL

  March 14, 2022, 1:54 PM – March 14, 2022, 2:06 PM

  Publication: arXiv:2108.06252

  Presenters

  • William Z Van Benschoten

    • University of Iowa

  Authors

  • William Z Van Benschoten

    • University of Iowa

  • James J Shepherd

    • University of Iowa

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• Rapid Generation of Optimal Generalized Monkhorst-Pack Grids

  ORAL

  March 14, 2022, 2:06 PM – March 14, 2022, 2:18 PM

  Publication: Wang, Y., Wisesa, P., Balasubramanian, A., Dwaraknath, S. and Mueller, T., 2021. Rapid generation of optimal generalized Monkhorst-Pack grids. Computational Materials Science, 187, p.110100.
  Wisesa, P., McGill, K.A. and Mueller, T., 2016. Efficient generation of generalized Monkhorst-Pack grids through the use of informatics. Physical Review B, 93(15), p.155109.

  Presenters

  • Yunzhe Wang

    • Johns Hopkins University

  Authors

  • Yunzhe Wang

    • Johns Hopkins University

  • Pandu Wisesa

    • Johns Hopkins University

  • Adarsh Balasubramanian

    • Johns Hopkins University

  • Shyam Dwaraknath

    • Lawrence Berkeley National Laboratory

  • Tim Mueller

    • Johns Hopkins University

  View abstract →