This title appears in the Scientific Report :
2017
Please use the identifier:
http://hdl.handle.net/2128/15976 in citations.
Exascale Scientific Applications: Programming Approaches for Scalability, Performance, and Portability: KKRnano
Exascale Scientific Applications: Programming Approaches for Scalability, Performance, and Portability: KKRnano
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 optimi...
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Personal Name(s): | Baumeister, Paul F. (Corresponding author) |
---|---|
Bornemann, Marcel / Zeller, Rudolf / Pleiter, Dirk | |
Contributing Institute: |
Theoretische Nanoelektronik; IAS-3 Quanten-Theorie der Materialien; IAS-1 Jülich Supercomputing Center; JSC |
Published in: |
Exascale scientific applications : scalability and performance portability / Straatsma, Tjerk P., ; Williams, Timothy J. ; Antypas, Katerina |
Imprint: |
Boca Raton, Florida, USA
Chapman and Hall/CRC
2017
|
Physical Description: |
431-448 |
ISBN: |
9781138197541 |
Document Type: |
Contribution to a book |
Research Program: |
Controlling Collective States Supercomputer Facility Computational Science and Mathematical Methods |
Series Title: |
Chapman & Hall/CRC computational science
1 |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
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. |