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Institution

National Center for Computational Sciences

About: National Center for Computational Sciences is a based out in . It is known for research contribution in the topics: Massively parallel & Supernova. The organization has 131 authors who have published 270 publications receiving 7196 citations.


Papers
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Journal ArticleDOI
TL;DR: Algorithm for efficient short range force calculation on hybrid high-performance machines, an approach for dynamic load balancing of work between CPU and accelerator cores, and the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators are described.

557 citations

Journal ArticleDOI
TL;DR: This work designs a low-depth version of the unitary coupled-cluster ansatz, uses the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent of the deuteron binding energy.
Abstract: We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent. Our work is the first step towards scalable nuclear structure computations on a quantum processor via the cloud, and it sheds light on how to map scientific computing applications onto nascent quantum devices.

391 citations

Journal ArticleDOI
TL;DR: This paper presents an efficient implementation of the particle–particle particle-mesh method based on the work by Harvey and De Fabritiis, and provides a performance comparison of the same kernels compiled with both CUDA and OpenCL.

381 citations

Journal ArticleDOI
Edoardo Aprà1, Eric J. Bylaska1, W. A. de Jong2, Niranjan Govind1, Karol Kowalski1, T. P. Straatsma3, Marat Valiev1, H. J. J. van Dam4, Yuri Alexeev5, J. Anchell6, V. Anisimov5, Fredy W. Aquino, Raymond Atta-Fynn7, Jochen Autschbach8, Nicholas P. Bauman1, Jeffrey C. Becca9, David E. Bernholdt10, K. Bhaskaran-Nair11, Stuart Bogatko12, Piotr Borowski13, Jeffery S. Boschen14, Jiří Brabec15, Adam Bruner16, Emilie Cauet17, Y. Chen18, Gennady N. Chuev19, Christopher J. Cramer20, Jeff Daily1, M. J. O. Deegan, Thom H. Dunning21, Michel Dupuis8, Kenneth G. Dyall, George I. Fann10, Sean A. Fischer22, Alexandr Fonari23, Herbert A. Früchtl24, Laura Gagliardi20, Jorge Garza25, Nitin A. Gawande1, Soumen Ghosh20, Kurt R. Glaesemann1, Andreas W. Götz26, Jeff R. Hammond6, Volkhard Helms27, Eric D. Hermes28, Kimihiko Hirao, So Hirata29, Mathias Jacquelin2, Lasse Jensen9, Benny G. Johnson, Hannes Jónsson30, Ricky A. Kendall10, Michael Klemm6, Rika Kobayashi31, V. Konkov32, Sriram Krishnamoorthy1, M. Krishnan18, Zijing Lin33, Roberto D. Lins34, Rik J. Littlefield, Andrew J. Logsdail35, Kenneth Lopata36, Wan Yong Ma37, Aleksandr V. Marenich20, J. Martin del Campo38, Daniel Mejía-Rodríguez39, Justin E. Moore6, Jonathan M. Mullin, Takahito Nakajima, Daniel R. Nascimento1, Jeffrey A. Nichols10, P. J. Nichols40, J. Nieplocha1, Alberto Otero-de-la-Roza41, Bruce J. Palmer1, Ajay Panyala1, T. Pirojsirikul42, Bo Peng1, Roberto Peverati32, Jiri Pittner15, L. Pollack, Ryan M. Richard43, P. Sadayappan44, George C. Schatz45, William A. Shelton36, Daniel W. Silverstein46, D. M. A. Smith6, Thereza A. Soares47, Duo Song1, Marcel Swart, H. L. Taylor48, G. S. Thomas1, Vinod Tipparaju49, Donald G. Truhlar20, Kiril Tsemekhman, T. Van Voorhis50, Álvaro Vázquez-Mayagoitia5, Prakash Verma, Oreste Villa51, Abhinav Vishnu1, Konstantinos D. Vogiatzis52, Dunyou Wang53, John H. Weare26, Mark J. Williamson54, Theresa L. Windus14, Krzysztof Wolinski13, A. T. Wong, Qin Wu4, Chan-Shan Yang2, Q. Yu55, Martin Zacharias56, Zhiyong Zhang57, Yan Zhao58, Robert W. Harrison59 
Pacific Northwest National Laboratory1, Lawrence Berkeley National Laboratory2, National Center for Computational Sciences3, Brookhaven National Laboratory4, Argonne National Laboratory5, Intel6, University of Texas at Arlington7, State University of New York System8, Pennsylvania State University9, Oak Ridge National Laboratory10, Washington University in St. Louis11, Wellesley College12, Maria Curie-Skłodowska University13, Iowa State University14, Academy of Sciences of the Czech Republic15, University of Tennessee at Martin16, Université libre de Bruxelles17, Facebook18, Russian Academy of Sciences19, University of Minnesota20, University of Washington21, United States Naval Research Laboratory22, Georgia Institute of Technology23, University of St Andrews24, Universidad Autónoma Metropolitana25, University of California, San Diego26, Saarland University27, Sandia National Laboratories28, University of Illinois at Urbana–Champaign29, University of Iceland30, Australian National University31, Florida Institute of Technology32, University of Science and Technology of China33, Oswaldo Cruz Foundation34, Cardiff University35, Louisiana State University36, Chinese Academy of Sciences37, National Autonomous University of Mexico38, University of Florida39, Los Alamos National Laboratory40, University of Oviedo41, Prince of Songkla University42, Ames Laboratory43, University of Utah44, Northwestern University45, Universal Display Corporation46, Federal University of Pernambuco47, CD-adapco48, Cray49, Massachusetts Institute of Technology50, Nvidia51, University of Tennessee52, Shandong Normal University53, University of Cambridge54, Advanced Micro Devices55, Technische Universität München56, Stanford University57, Wuhan University of Technology58, Stony Brook University59
TL;DR: The NWChem computational chemistry suite is reviewed, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.
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.

342 citations

Journal ArticleDOI
TL;DR: In this paper, the authors performed ab initio neutrino radiation hydrodynamics simulations in three and two spatial dimensions (3D and 2D) of core-collapse supernovae from the same 15 M⊙ progenitor through 440 ms after core bounce.
Abstract: We have performed ab initio neutrino radiation hydrodynamics simulations in three and two spatial dimensions (3D and 2D) of core-collapse supernovae from the same 15 M⊙ progenitor through 440 ms after core bounce. Both 3D and 2D models achieve explosions; however, the onset of explosion (shock revival) is delayed by ~100 ms in 3D relative to the 2D counterpart and the growth of the diagnostic explosion energy is slower. This is consistent with previously reported 3D simulations utilizing iron-core progenitors with dense mantles. In the ~100 ms before the onset of explosion, diagnostics of neutrino heating and turbulent kinetic energy favor earlier explosion in 2D. During the delay, the angular scale of convective plumes reaching the shock surface grows and explosion in 3D is ultimately lead by a single, large-angle plume, giving the expanding shock a directional orientation not dissimilar from those imposed by axial symmetry in 2D simulations. Finally, we posit that shock revival and explosion in the 3D simulation may be delayed until sufficiently large plumes form, whereas such plumes form more rapidly in 2D, permitting earlier explosions.

296 citations


Authors

Showing all 131 results

NameH-indexPapersCitations
Yangkang Chen462546551
Zhe Zhang38904211
Barbara Chapman342727080
Georgia D. Tourassi342174844
Jan-Michael Y. Carrillo321072895
John F. Ankner311373505
Rajeev Kumar27952094
Galen M. Shipman27832103
Ramanan Sankaran27853715
S. Michael Kilbey261052233
Gustav R. Jansen26563143
Youngjae Kim261343019
Jack C. Wells261331747
David M. Rogers261022775
Mark Berrill251092084
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202140
202030
201915
201825
201724
201617