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A Methodology For Developing High Performance Computing Models: Storm-Scale Weather Prediction, Nikos Chrisochoides, Kelvin Droegemeier, Geoffrey C. Fox, Kim Mills, Ming Xue
A Methodology For Developing High Performance Computing Models: Storm-Scale Weather Prediction, Nikos Chrisochoides, Kelvin Droegemeier, Geoffrey C. Fox, Kim Mills, Ming Xue
Northeast Parallel Architecture Center
A methodology for developing future generations of a storm-scale weather prediction model for Massively Parallel Processing is described. The forecast model is the Advanced Regional Prediction System (ARPS), a three-dimensional, fully compressible, non-hydrostatic predictive model. In the short term, the computational goals include developing a portable, scalable model for distributed memory SIMD and MIMD architectures, while preserving a high degree of modularity to support rapid design and validation, maintainability, educational goals and operational testing. Longer term computational goals include a parallel adaptive mesh refinement scheme. A FortranD/High Performance Fortran version of the ARPS provides portability in the current version of …