Exascale applications: skin in the game

Author:

Alexander Francis1,Almgren Ann2,Bell John2,Bhattacharjee Amitava3,Chen Jacqueline4,Colella Phil2,Daniel David5,DeSlippe Jack2,Diachin Lori6,Draeger Erik6,Dubey Anshu7,Dunning Thom8,Evans Thomas9,Foster Ian7,Francois Marianne5,Germann Tim5,Gordon Mark10,Habib Salman7,Halappanavar Mahantesh8,Hamilton Steven9,Hart William4,(Henry) Huang Zhenyu8,Hungerford Aimee5,Kasen Daniel2,Kent Paul R. C.9,Kolev Tzanio6,Kothe Douglas B.9,Kronfeld Andreas11,Luo Ye7,Mackenzie Paul11,McCallen David2,Messer Bronson9,Mniszewski Sue5,Oehmen Chris8,Perazzo Amedeo12,Perez Danny5,Richards David6,Rider William J.4,Rieben Rob6,Roche Kenneth8,Siegel Andrew7,Sprague Michael13,Steefel Carl2,Stevens Rick7,Syamlal Madhava14,Taylor Mark4,Turner John9,Vay Jean-Luc2,Voter Artur F.5,Windus Theresa L.10,Yelick Katherine2

Affiliation:

1. Brookhaven National Laboratory, Upton, NY, USA

2. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

3. Princeton Plasma Physics Laboratory, Princeton, NJ, USA

4. Sandia National Laboratories, Albuquerque, NM, USA

5. Los Alamos National Laboratory, Los Alamos, NM, USA

6. Lawrence Livermore National Laboratory, Livermore, CA, USA

7. Argonne National Laboratory, Argonne, IL, USA

8. Pacific Northwest National Laboratory, Richland, WA, USA

9. Oak Ridge National Laboratory, Oak Ridge, TN, USA

10. Ames Laboratory, Ames, IA, USA

11. Fermi National Accelerator Laboratory, Batavia, IL, USA

12. SLAC National Accelerator Laboratory, Menlo Park, CA, USA

13. National Renewable Energy Laboratory, Golden, CO, USA

14. National Energy Technology Laboratory, Morgantown, WV, USA

Abstract

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’.

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Reference62 articles.

1. Exascale Computing in the United States

2. Asanovic K et al. 2016 The landscape of parallel computing research: a view from Berkeley. University of California at Berkeley. Technical Report No. UCB/EECS-2006-183.

3. Foster I et al. 2017 Computing just what you need: online data analysis and reduction at extreme scales. In European conference on parallel processing pp. 3–19. Berlin Germany: Springer.

4. AMReX: a framework for block-structured adaptive mesh refinement

5. Scalability of high-performance PDE solvers;Fischer P;Int. J. High Perform. Comput. Appl

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