DocumentCode :
668164
Title :
Highly optimized full GPU-acceleration of non-hydrostatic weather model SCALE-LES
Author :
Wahib, Mohamed ; Maruyama, Naoya
Author_Institution :
RIKEN Adv. Inst. for Comput. Sci., Kobe, Japan
fYear :
2013
fDate :
23-27 Sept. 2013
Firstpage :
1
Lastpage :
8
Abstract :
SCALE-LES is a non-hydrostatic weather model developed at RIKEN, Japan. It is intended to be a global high-resolution model that would be scaled to exascale systems. This paper introduces the full GPU acceleration of all SCALE-LES modules. Moreover, the paper demonstrates the strategies to handle the unique challenges of accelerating SCALE-LES using GPU. The proposed acceleration is important for identifying the expectations and requirements of scaling SCALE-LES, and similar real world applications, into the exascale era. The GPU implementation includes the optimized GPU acceleration of SCALE-LES for a single GPU with both CUDA Fortran and OpenACC. It also includes scaling SCALE-LES for GPU-accelerated clusters. The results and analysis show how the optimization strategies affect the performance gain in SCALE-LES when moving from conventional CPU clusters towards GPU-powered clusters.
Keywords :
FORTRAN; geophysics computing; graphics processing units; parallel architectures; weather forecasting; CPU cluster; CUDA Fortran; GPU implementation; GPU-accelerated cluster; Japan; OpenACC; RIKEN; SCALE-LES module; exascale system; global high-resolution model; highly optimized full GPU-acceleration; nonhydrostatic weather model; optimization strategy; performance gain; single GPU; Acceleration; Computational modeling; Graphics processing units; Instruction sets; Kernel; Meteorology; Registers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cluster Computing (CLUSTER), 2013 IEEE International Conference on
Conference_Location :
Indianapolis, IN
Type :
conf
DOI :
10.1109/CLUSTER.2013.6702667
Filename :
6702667
Link To Document :
بازگشت