Title
A Methodology For Developing High Performance Computing Models: Storm-Scale Weather Prediction
Document Type
Article
Date
1993
Keywords
High Performance Computing Models, Storm-Scale Weather Prediction, Massively Parallel Processing, Advanced Regional Prediction System, ARPS, SIMD architecture, MIMD architecture, Fortran D, High Performance Fortran
Language
English
Disciplines
Computer Sciences | Meteorology | Programming Languages and Compilers
Description/Abstract
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 the model, and supports future model research goals.
Recommended Citation
Chrisochoides, Nikos; Droegemeier, Kelvin; Fox, Geoffrey C.; Mills, Kim; and Xue, Ming, "A Methodology For Developing High Performance Computing Models: Storm-Scale Weather Prediction" (1993). Northeast Parallel Architecture Center. 86.
https://surface.syr.edu/npac/86
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
