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1. NWChem: Past, Present, and Future

Author

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 Jr., T. H., Dupuis, M., Dyall, K. G., Fann, G. I., Fischer, S. A., Fonari, A., Früuchtl, 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., del Campo, J. Martin, Mejia-Rodriguez, D., Moore, J. E., Mullin, J. M., Nakajima, T., Nascimento, D. R., Nichols, J. A., Nichols, P. J., Nieplocha, J., de la Roza, A. Otero, Palmer, B., Panyala, A., Pirojsirikul, T., Peng, B., Peverati, R., Pittner, J., Pollack, L., Richard, R. M., 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, Á., Verma, P., Villa, O., Vishnu, A., Vogiatzis, K. D., Wang, D., Weare, J. H., Williamson, M. J., Windus, T. L., Woliński, K., Wong, A. T., Wu, Q., Yang, C., Yu, Q., Zacharias, M., Zhang, Z., Zhao, Y., and Harrison, R. J.

Subjects
Physics - Chemical Physics, Physics - Computational Physics
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-principledriven methodologies to model complex chemical and materials processes. Over the last 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., Comment: This article appeared in volume 152, issue 18, page 184102 of the Journal of Chemical Physics. It can be found at https://doi.org/10.1063/5.0004997

Published
2020
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2. NWChem: Past, present, and future

Author

Aprà, E, Bylaska, EJ, De Jong, WA, Govind, N, Kowalski, K, Straatsma, TP, Valiev, M, Van Dam, HJJ, Alexeev, Y, Anchell, J, Anisimov, V, Aquino, FW, Atta-Fynn, R, Autschbach, J, Bauman, NP, Becca, JC, Bernholdt, DE, Bhaskaran-Nair, K, Bogatko, S, Borowski, P, Boschen, J, Brabec, J, Bruner, A, Cauët, E, Chen, Y, Chuev, GN, Cramer, CJ, Daily, J, Deegan, MJO, Dunning, TH, Dupuis, M, Dyall, KG, Fann, GI, Fischer, SA, Fonari, A, Früchtl, H, Gagliardi, L, Garza, J, Gawande, N, Ghosh, S, Glaesemann, K, Götz, AW, Hammond, J, Helms, V, Hermes, ED, Hirao, K, Hirata, S, Jacquelin, M, Jensen, L, Johnson, BG, Jónsson, H, Kendall, RA, Klemm, M, Kobayashi, R, Konkov, V, Krishnamoorthy, S, Krishnan, M, Lin, Z, Lins, RD, Littlefield, RJ, Logsdail, AJ, Lopata, K, Ma, W, Marenich, AV, Martin Del Campo, J, Mejia-Rodriguez, D, Moore, JE, Mullin, JM, Nakajima, T, Nascimento, DR, Nichols, JA, Nichols, PJ, Nieplocha, J, Otero-De-La-Roza, A, Palmer, B, Panyala, A, Pirojsirikul, T, Peng, B, Peverati, R, Pittner, J, Pollack, L, Richard, RM, Sadayappan, P, Schatz, GC, Shelton, WA, Silverstein, DW, Smith, DMA, Soares, TA, Song, D, Swart, M, Taylor, HL, Thomas, GS, Tipparaju, V, Truhlar, DG, Tsemekhman, K, Van Voorhis, T, Vázquez-Mayagoitia, A, Verma, P, Villa, O, and Vishnu, A

Subjects
physics.chem-ph, physics.comp-ph, Physical Sciences, Chemical Sciences, Engineering, Chemical Physics
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

3. NWChem

Author

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

4. PluginPlay: Enabling exascale scientific software one module at a time.

Author

Richard RM, Keipert K, Waldrop J, Keçeli M, Williams-Young D, Bair R, Boschen J, Crandall Z, Gasperich K, Mahmud QI, Panyala A, Valeev E, van Dam H, de Jong WA, and Windus TL

Abstract

For many computational chemistry packages, being able to efficiently and effectively scale across an exascale cluster is a heroic feat. Collective experience from the Department of Energy's Exascale Computing Project suggests that achieving exascale performance requires far more planning, design, and optimization than scaling to petascale. In many cases, entire rewrites of software are necessary to address fundamental algorithmic bottlenecks. This in turn requires a tremendous amount of resources and development time, resources that cannot reasonably be afforded by every computational science project. It thus becomes imperative that computational science transition to a more sustainable paradigm. Key to such a paradigm is modular software. While the importance of modular software is widely recognized, what is perhaps not so widely appreciated is the effort still required to leverage modular software in a sustainable manner. The present manuscript introduces PluginPlay, https://github.com/NWChemEx-Project/PluginPlay, an inversion-of-control framework designed to facilitate developing, maintaining, and sustaining modular scientific software packages. This manuscript focuses on the design aspects of PluginPlay and how they specifically influence the performance of the resulting package. Although, PluginPlay serves as the framework for the NWChemEx package, PluginPlay is not tied to NWChemEx or even computational chemistry. We thus anticipate PluginPlay to prove to be a generally useful tool for a number of computational science packages looking to transition to the exascale., (© 2023 Author(s). Published under an exclusive license by AIP Publishing.)

Published
2023
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