1. NWChem
- Author
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Aprà, E., Bylaska, E. J., de Jong, W. A., Govind, N., Kowalski, K., Straatsma, T. P., Valiev, M., van Dam, H. J.J., Alexeev, Y., Anchell, J., Anisimov, V., Aquino, F. W., Atta-Fynn, R., Autschbach, J., Bauman, N. P., Becca, J. C., Bernholdt, D. E., Bhaskaran-Nair, K., Bogatko, S., Borowski, P., Boschen, J., Brabec, J., Bruner, A., Cauët, E., Chen, Y., Chuev, G. N., Cramer, C. J., Daily, J., Deegan, M. J.O., Dunning, T. H., Dupuis, M., Dyall, K. G., Fann, G. I., Fischer, S. A., Fonari, A., Früchtl, H., Gagliardi, L., Garza, J., Gawande, N., Ghosh, S., Glaesemann, K., Götz, A. W., Hammond, J., Helms, V., Hermes, E. D., Hirao, K., Hirata, S., Jacquelin, M., Jensen, L., Johnson, B. G., Jónsson, H., Kendall, R. A., Klemm, M., Kobayashi, R., Konkov, V., Krishnamoorthy, S., Krishnan, M., Lin, Z., Lins, R. D., Littlefield, R. J., Logsdail, A. J., Lopata, K., Ma, W., Marenich, A. V., Martin Del Campo, J., Mejia-Rodriguez, D., Moore, J. E., Mullin, J. M., Nakajima, T., Nascimento, D. R., Nichols, J. A., Nichols, P. J., Nieplocha, J., Otero-de-la-Roza, A., Palmer, B., Panyala, A., Pirojsirikul, T., Peng, B., Peverati, R., Pittner, J., Pollack, L., Sadayappan, P., Schatz, G. C., Shelton, W. A., Silverstein, D. W., Smith, D. M.A., Soares, T. A., Song, D., Swart, M., Taylor, H. L., Thomas, G. S., Tipparaju, V., Truhlar, D. G., Tsemekhman, K., Van Voorhis, T., Vázquez-Mayagoitia, Verma, P., Villa, O., Vishnu, A., Vogiatzis, K. D., Wang, Dunyou, Weare, J. H., Williamson, M. J., Windus, T. L., Woliński, K., Wong, A. T., Wu, Q., Yang, C., Yu, Q., Zacharias, M., Zhang, Zhiyong, Zhao, Yan, Harrison, R. J., Pacific Northwest National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Brookhaven National Laboratory, Argonne National Laboratory, Intel, University of Texas at Arlington, The State University of New York at Buffalo, Pennsylvania State University, Washington University St. Louis, Maria Curie-Sklodowska University, Iowa State University, Czech Academy of Sciences, University of Tennessee System, Université Libre de Bruxelles, Facebook Inc, Russian Academy of Sciences, University of Minnesota Twin Cities, Jodrell Bank Observatory, University of Washington, Dirac Solutions, Naval Research Laboratory, Georgia Institute of Technology, University of St Andrews, Universidad Autónoma Metropolitana, University of California San Diego, Saarland University, Sandia National Laboratories, RIKEN, University of Illinois at Urbana-Champaign, Multiscale Statistical and Quantum Physics, Australian National University, Florida Institute of Technology, University of Science and Technology of China, Fundação Oswaldo Cruz, Zerene Systems LLC, Cardiff University, Louisiana State University, CAS - Institute of Software, Universidad Nacional Autónoma de México, University of Florida, Los Alamos National Laboratory, University of Oviedo, Prince of Songkla University, University of Utah, Northwestern University, Universal Display Corporation, Universidade Federal de Pernambuco, ICREA, Cray Inc, Massachusetts Institute of Technology, 1QBit, Nvidia, University of Tennessee, Knoxville, Shandong Normal University, University of Cambridge, Advanced Micro Devices, Technische Universität München, Stanford University, Wuhan University of Technology, Stony Brook University, Department of Applied Physics, Aalto-yliopisto, and Aalto University
- Abstract
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.
- Published
- 2020