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Materials and Molecular Modeling at the Exascale

Authors :
Thomas W. Keal
Alin-Marin Elena
Alexey A. Sokol
Karen Stoneham
Matt I. J. Probert
Clotilde S. Cucinotta
David J. Willock
Andrew J. Logsdail
Andrea Zen
Phil J. Hasnip
Ian J. Bush
Matthew Watkins
Dario Alfe
Chris-Kriton Skylaris
Basile F. E. Curchod
Qiong Cai
Scott M. Woodley
Keal, T. W.
Elena, A. -M.
Sokol, A. A.
Stoneham, K.
Probert, M. I. J.
Cucinotta, C. S.
Willock, D. J.
Logsdail, A. J.
Zen, A.
Hasnip, P. J.
Bush, I. J.
Watkins, M.
Alfe', D.
Skylaris, C. -K.
Curchod, B. F. E.
Cai, Q.
Woodley, S. M.
Source :
Computing in Science & Engineering. 24:36-45
Publication Year :
2022
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2022.

Abstract

Progression of computational resources towards exascale computing makes possible simulations of unprecedented accuracy and complexity in the fields of materials and molecular modelling (MMM), allowing high fidelity in silico experiments on complex materials of real technological interest. However, this presents demanding challenges for the software used, especially the exploitation of the huge degree of parallelism available on exascale hardware, and the associated problems of developing effective workflows and data management on such platforms. As part of the UKs ExCALIBUR exascale computing initiative, the UK-led MMM Design and Development Working Group has worked with the broad MMM community to identify a set of high priority application case studies which will drive future exascale software developments. We present an overview of these case studies, categorized by the methodological challenges which will be required to realize them on exascale platforms, and discuss the exascale requirements, software challenges and impact of each application area.

Details

ISSN :
1558366X and 15219615
Volume :
24
Database :
OpenAIRE
Journal :
Computing in Science & Engineering
Accession number :
edsair.doi.dedup.....5814ea7b78d032ac58cd5220cd30ea1e
Full Text :
https://doi.org/10.1109/mcse.2022.3141328