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| Home > Publications database > Exascale Scientific Applications: Programming Approaches for Scalability, Performance, and Portability: KKRnano > print |
| 001 | 840228 | ||
| 005 | 20240625095029.0 | ||
| 010 | _ | _ | |a 2017021706 |
| 020 | _ | _ | |a 9781138197541 |
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| 037 | _ | _ | |a FZJ-2017-07782 |
| 041 | _ | _ | |a English |
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| 100 | 1 | _ | |a Baumeister, Paul F. |0 P:(DE-Juel1)156619 |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a Exascale Scientific Applications: Programming Approaches for Scalability, Performance, and Portability: KKRnano |
| 260 | _ | _ | |a Boca Raton, Florida, USA |c 2017 |b Chapman and Hall/CRC |
| 295 | 1 | 0 | |a Exascale scientific applications : scalability and performance portability / Straatsma, Tjerk P., ; Williams, Timothy J. ; Antypas, Katerina |
| 300 | _ | _ | |a 431-448 |
| 336 | 7 | _ | |a BOOK_CHAPTER |2 ORCID |
| 336 | 7 | _ | |a Book Section |0 7 |2 EndNote |
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| 490 | 0 | _ | |a Chapman & Hall/CRC computational science |v 1 |
| 520 | _ | _ | |a Addressing certain materials science problems, e.g. inhomogeneous materials, using Density Functional Theory will require exascale compute capabilities as a sufficiently large number of atoms need to be simulated. In this chapter we consider a particular approach and an implementation that is optimized for extreme scale parallelism. We provide an overview on the Kohn-Sham approach as well as its application areas and discuss in detail the application KKRnano. Here we focus on recent efforts to port this application to GPU-accelerated architectures. |
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