Authors

E. Aprà, Pacific Northwest National Laboratory
E. J. Bylaska, Pacific Northwest National Laboratory
W. A. De Jong, Lawrence Berkeley National Laboratory
N. Govind, Pacific Northwest National Laboratory
K. Kowalski, Pacific Northwest National Laboratory
T. P. Straatsma, Oak Ridge National Laboratory
M. Valiev, Pacific Northwest National Laboratory
H. J.J. Van Dam, Brookhaven National Laboratory
Y. Alexeev, Argonne National Laboratory
J. Anchell, Intel Corporation
V. Anisimov, Argonne National Laboratory
F. W. Aquino, QSimulate Incorporated
R. Atta-Fynn, The University of Texas at Arlington
J. Autschbach, University at Buffalo, The State University of New York
N. P. Bauman, Pacific Northwest National Laboratory
J. C. Becca, Pennsylvania State University
D. E. Bernholdt, Oak Ridge National Laboratory
K. Bhaskaran-Nair, Washington University in St. Louis
S. Bogatko
P. Borowski, Maria Curie-Sklodowska University in Lublin
J. Boschen, Iowa State University
J. Brabec, Academy of Sciences of the Czech Republic
A. Bruner, University of Tennessee
E. Cauët, Université libre de Bruxelles (ULB)
Y. Chen, Facebook, Inc.
G. N. Chuev, Institute of Theoretical and Experimental Biophysics of the Russian Academy of Sciences
C. J. Cramer, University of Minnesota Twin Cities
J. Daily, Pacific Northwest National Laboratory
M. J.O. Deegan, The University of Manchester
T. H. Dunning, University of Washington, Seattle
M. Dupuis, University at Buffalo, The State University of New York
K. G. Dyall, Dirac Solutions
G. I. Fann, Oak Ridge National Laboratory

Document Type

Article

Publication Date

5-14-2020

Abstract

© 2020 U.S. Government. Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

Publication Source (Journal or Book title)

Journal of Chemical Physics

COinS