Maximizing Multi-Core Performance of the Weather Research and Forecast Model Over the Hawaiian Islands

Kevin P. Roe (Maui High Performance Computing Center), Duane Stevens (University of Hawaii at Manoa)

Keywords: imaging

Abstract:

The Hawaiian Islands consist of dramatic terrain changes over short distances, resulting in a variety of microclimates in close proximity. To handle these challenging conditions, weather models must be run at very fine vertical and horizontal resolutions to produce accurate forecasts. Computational demands require WRF to be executed in parallel on the Maui High Performance Computing Centers Mana system, a PowerEdge M610 Linux cluster. This machine has 1,152 compute nodes, each with two 2.8 GHz quad-core Intel Nehalem processors and 24 GB RAM. Realizing maximum performance on Mana relied on the determination of an optimal number of cores to use per socket, the efficiency of an MPI only implementation, an optimal set of parameters for adaptive time stepping, a way to meet the strict stability requirements necessary for Hawaii, effective choices for processor and memory affinity, and parallel automation techniques for producing forecast imagery.

Date of Conference: September 14-17, 2010

Track: Posters

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