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Exascale applications: skin in the game
Author(s) -
Francis J. Alexander,
Ann Almgren,
John B. Bell,
A. Bhattacharjee,
Jacqueline Chen,
Phil Colella,
David Daniel,
Jack Deslippe,
Lori Freitag Diachin,
Erik W. Draeger,
Anshu Dubey,
Thom H. Dunning,
Thomas Evans,
Ian Foster,
Marianne Francois,
Timothy C. Germann,
Mark S. Gordon,
Salman Habib,
Mahantesh Halappanavar,
Steven Hamilton,
William E. Hart,
Zhenyu Huang,
Aimee Hungerford,
Daniel Kasen,
Paul R. C. Kent,
Tzanio Kolev,
Douglas B. Kothe,
Andreas S. Kronfeld,
Ye Luo,
P. B. Mackenzie,
David McCallen,
O. E. Bronson Messer,
Sue Mniszewski,
Chris Oehmen,
Amedeo Perazzo,
Danny Pérez,
David F. Richards,
William J. Rider,
Rob Rieben,
Kenneth J. Roche,
Andrew Siegel,
Michael Sprague,
Carl I. Steefel,
Rick Stevens,
Madhava Syamlal,
Mark A. Taylor,
John Turner,
Jean-Luc Vay,
Artur F. Voter,
Theresa L. Windus,
Katherine Yelick
Publication year - 2020
Publication title -
philosophical transactions of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.074
H-Index - 169
eISSN - 1471-2962
pISSN - 1364-503X
DOI - 10.1098/rsta.2019.0056
Subject(s) - computer science , exploit , metaphor , field (mathematics) , exascale computing , data science , computer security , supercomputer , parallel computing , pure mathematics , philosophy , linguistics , mathematics
As noted in Wikipedia, skin in the game refers to having ‘incurred risk by being involved in achieving a goal’, where ‘ skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion’. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

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