Scalability of Semi-implicit Time Integrators for Nonhydrostatic Galerkin-Based Atmospheric Models on Large Scale Clusters
Cluster Computing（2011）
摘要
We describe our ongoing effort to optimize a next-generation atmospheric model based on the continuous Galerkin, or spectral element, method: the Nonhydrostatic Unified Model of the Atmosphere (NUMA), which is targeted towards large cluster architectures. The linear solver within a distributed memory paradigm is critical for overall model efficiency. The goal of this work-in-progress is to investigate the scalability of the model for different solvers and determine a set of optimal solvers to be used for different situations. We will describe our novel approach and demonstrate its scalability on a variety of clusters of multicore node clusters. We also present performance statistics to explain the scalability behavior.
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关键词
nonhydrostatic galerkin-based atmospheric models,linear solver,large scale clusters,large cluster architecture,optimal solvers,different situation,scalability behavior,different solvers,next-generation atmospheric model,continuous galerkin,overall model efficiency,semi-implicit time integrators,nonhydrostatic unified model,scalability,architecture,mathematical model,performance,hydrostatics,efficiency,statistics,mpi,computational fluid dynamics,computational modeling,distribution,clustering,gravity,atmospheric modeling,galerkin method,atmospheric models
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