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| Titel |
Development of efficient GPU parallelization of WRF Yonsei University planetary boundary layer scheme |
| VerfasserIn |
M. Huang, J. Mielikainen, B. Huang, H. Chen, H.-L. A. Huang, M. D. Goldberg |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 9 ; Nr. 8, no. 9 (2015-09-30), S.2977-2990 |
| Datensatznummer |
250116564
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| Publikation (Nr.) |
 copernicus.org/gmd-8-2977-2015.pdf |
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| Zusammenfassung |
| The planetary boundary layer (PBL) is the lowest part of the
atmosphere and where its character is directly affected by its
contact with the underlying planetary surface. The PBL is
responsible for vertical sub-grid-scale fluxes due to eddy transport
in the whole atmospheric column. It determines the flux profiles
within the well-mixed boundary layer and the more stable layer
above. It thus provides an evolutionary model of atmospheric
temperature, moisture (including clouds), and horizontal momentum in
the entire atmospheric column. For such purposes, several PBL models
have been proposed and employed in the weather research and
forecasting (WRF) model of which the Yonsei University (YSU) scheme
is one. To expedite weather research and prediction, we have put
tremendous effort into developing an accelerated implementation of
the entire WRF model using graphics processing unit (GPU) massive
parallel computing architecture whilst maintaining its accuracy as
compared to its central processing unit (CPU)-based implementation. This paper presents our
efficient GPU-based design on a WRF YSU PBL scheme. Using one NVIDIA
Tesla K40 GPU, the GPU-based YSU PBL scheme achieves a speedup of
193× with respect to its CPU
counterpart running on one CPU core, whereas the speedup for one CPU
socket (4 cores) with respect to 1 CPU core is only
3.5×. We can even boost the speedup to 360× with
respect to 1 CPU core as two K40 GPUs are applied. |
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