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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.

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