NWChemEx – Computational Chemistry for the Exascale Era

ORAL

Abstract

NWChemEx is an ECP project for computational chemistry that builds on the success of NWChem. NWChem is an early co-design project started in 1992, to address distributed memory parallel computers. The code's modular design, the Global Arrays for distributed data handling, and code generation using the Tensor Contraction Engine, provided a platform for building scalable chemistry capabilities. Key capabilities of the code are MD, DFT methods, and coupled cluster.
The science challenges targeted by the NWChemEx are accurate simulations of catalytic reactions and biomolecular complexes. Such calculations require next generation computers that are very different from those NWChem was designed for. Hence, NWChemEx re-engineered the concepts, models and implementations for future computers. We focus on overcoming the limitations of NWChem’s design. This involves platform enhancements like execution schedule aware tensor frameworks, composable simulations, code generation for accelerator hardware, and exploiting emerging sparsity. The required changes in the key methods will be discussed.

*This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.

–

Presenters

  • Hubertus van Dam

    • Condensed Matter Physics and Materials Science, Brookhaven National Laboratory

Authors

  • Hubertus van Dam

    • Condensed Matter Physics and Materials Science, Brookhaven National Laboratory

  • Edoardo Apra

    • Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory

  • Raymond Bair

    • Computational Science, Argonne National Laboratory

  • Jeffery S Boschen

    • Chemistry, Iowa State University

  • Eric J. Bylaska

    • Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory

  • Wibe A De Jong

    • Computational Research Division, Lawrence Berkeley National Laboratory
    • Lawrence Berkeley National Laboratory
    • Computational Chemistry, Materials and Climate Group, Lawrence Berkeley National Laboratory

  • Thomas H Dunning

    • Advanced Computing, Math & Data, Pacific Northwest National Laboratory

  • Niranjan Govind

    • Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory

  • Robert J Harrison

    • Institute for Advance Computational Science, Stony Brook University

  • Kristopher Keipert

    • Nvidia

  • Karol Kowalski

    • PNNL
    • Pacific Northwest National Laboratory
    • Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory

  • Sriram Krishnamoorthy

    • High Performance Computing, Pacific Northwest National Laboratory

  • Suraj Kumar

    • High Performance Computing, Pacific Northwest National Laboratory

  • Erdal Mutlu

    • High Performance Computing, Pacific Northwest National Laboratory

  • Bruce Palmer

    • High Performance Computing, Pacific Northwest National Laboratory

  • Ajay Panyala

    • High Performance Computing, Pacific Northwest National Laboratory

  • Bo Peng

    • Computational Engineering, Pacific Northwest National Laboratory

  • Ryan M Richard

    • Chemical & Biological Sciences, Ames Laboratory

  • T P Straatsma

    • Oak Ridge National Laboratory

  • Edward F Valeev

    • Department of Chemistry, Virginia Tech

  • Marat Valiev

    • Biosystems Dynamics & Simulation, Pacific Northwest National Laboratory

  • David B Williams-Young

    • Scalable Solvers Group, Lawrence Berkeley National Laboratory

  • Chao Yang

    • Scalable Solvers Group, Lawrence Berkeley National Laboratory
    • Lawrence Berkeley National Laboratory

  • Theresa L Windus

    • Chemistry, Iowa State University