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GPU Computing for Atmospheric Modeling
July/August 2010 (vol. 12 no. 4)
pp. 26-33
ASCII Text
x 
 
Rory Kelly, "GPU Computing for Atmospheric Modeling," Computing in Science and Engineering, vol. 12, no. 4, pp. 26-33, July/August, 2010.
 
 
BibTex
x
 
@article{ 10.1109/MCSE.2010.26,
author = {Rory Kelly},
title = {GPU Computing for Atmospheric Modeling},
journal ={Computing in Science and Engineering},
volume = {12},
number = {4},
issn = {1521-9615},
year = {2010},
pages = {26-33},
doi = {http://doi.ieeecomputersociety.org/10.1109/MCSE.2010.26},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - Computing in Science and Engineering
TI - GPU Computing for Atmospheric Modeling
IS - 4
SN - 1521-9615
SP26
EP33
EPD - 26-33
A1 - Rory Kelly,
PY - 2010
KW - emerging technologies
KW - threads
KW - graphics processors
KW - computations on discrete structures
VL - 12
JA - Computing in Science and Engineering
ER -
 
Rory Kelly, NCAR, Boulder
Much success has been achieved using GPUs to accelerate existing applications that are highly data parallel, or that are dominated by small, intense computational kernels. What are the prospects for porting existing large scientific models that do not fit this mold? We take an expensive routine from the CAM atmosphere model, and port it to a GPU using CUDA. We use the experience gained as a guide in thinking about porting the full application to an accelerator based system. We consider the best path forward for getting large scientific models running on accelerator based systems, and identify cases where porting may be feasible, and where a complete redesign may be the best option.

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Index Terms:
emerging technologies, threads, graphics processors, computations on discrete structures
Citation:
Rory Kelly, "GPU Computing for Atmospheric Modeling," Computing in Science and Engineering, vol. 12, no. 4, pp. 26-33, July-Aug. 2010, doi:10.1109/MCSE.2010.26
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