Scalability of Semi-Implicit Time Integrators for Nonhydrostatic Galerkin-based Atmospheric Models on Large Scale Cluster

Abstract

In this paper we describe the current status of our ongoing effort to optimize the efficiency of a novel application package for Nonhydrostatic Unified Model of the Atmosphere (NUMA) when running on 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.