Performance Analysis and Optimization of the Weather Research and Forecasting Model (WRF) on Intel Multicore and Manycore Architectures
Student: samuel J. Elliott (NCAR/CU Boulder)
Supervisor: Davide Del Vento (National Center for Atmospheric Research)
Abstract: The Weather Research and Forecasting (WRF) Model is a mesoscale numerical weather prediction system designed for both atmospheric research and operational forecasting needs. The WRF benchmarks used in this study were run on the Texas Advanced Computing Center (TACC) Stampede cluster, which utilizes Intel Xeon E5-2660 CPU’s and Xeon Phi SE10P coprocessors. Various aspects of WRF optimization were analyzed, many of which contributed significantly to optimization on Xeon Phi. These optimizations show that symmetric execution on Xeon and Xeon Phi can be used for highly efficient WRF simulations that significantly speed up execution relative to running on either homogeneous architecture. Performance analysis on Xeon Phi also exposes hybrid parallelization issues with the WRF model that are overlooked when running on architectures with fewer available threads per processing unit.
Two-page extended abstract: pdf