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SCHEDULE: NOV 15-20, 2015

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Performance Analysis and Optimization of the Weather Research and Forecasting Model (WRF) on Intel Multicore and Manycore Architectures

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, ACM Student Research Competition Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):samuel J. Elliott

ROOM:Level 4 - Lobby


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.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

samuel J. Elliott - NCAR/CU Boulder

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