SIParCS 2015- Samuel Elliott

Samuel Elliott, University of Colorado, Boulder

WRF Performance Optimization Targeting Intel Multicore and Manycore Architectures

(Slides)  (Recorded Talk)

The Weather Research and Forecasting (WRF) Model is a mesoscale numerical weather prediction system designed for both atmospheric research and operational forecasting needs. The 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. Many 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.

Mentors: Davide Del Vento and Siddhartha Ghosh, CISL