The schemes of cumulus parameterization are responsible for the sub-grid-scale effects of convective and/or shallow clouds, and intended to represent vertical fluxes due to unresolved updrafts and downdrafts and compensating motion outside the clouds. Some schemes additionally provide cloud and precipitation field tendencies in the convective column, and momentum tendencies due to convective transport of momentum. The schemes all provide the convective component of surface rainfall. Betts-Miller-Janjic (BMJ) is one scheme to fulfill such purposes in the weather research and forecast (WRF) model. National Centers for Environmental Prediction (NCEP) has tried to optimize the BMJ scheme for operational application. As there are no interactions among horizontal grid points, this scheme is very suitable for parallel computation. With the advantage of Intel Xeon Phi Many Integrated Core (MIC) architecture, efficient parallelization and vectorization essentials, it allows us to optimize the BMJ scheme. If compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670, the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.4x and 17.0x, respectively.

Date Published: 20 October 2015
PDF: 13 pages
Proc. SPIE 9646, High-Performance Computing in Remote Sensing V, 96460O (20 October 2015); doi: 10.1117/12.2196554

Published in SPIE Proceedings Vol. 9646:
High-Performance Computing in Remote Sensing V
Bormin Huang D.D.S.; Sebastián López; Zhensen Wu; Jose M. Nascimento; Boris A. Alpatov; Jordi Portell de Mora, Editor(s)