Optimization of the NMS6b Weather Model Code

Abstract

The U.S. Army needs timely and accurate weather forecasting to support the prediction of battlefield conditions. The U.S. Army Research Laboratory Major Shared Resource Center was tasked with optimizing the Nonhydrostatic Model Simulation (NMS) weather forecasting code for potential U.S. Army use. This code was written for parallel execution on shared memory architectures using OpenMP directives. As written, the code does not run on distributed memory nodes. The NMS code consist of tilde190,000 lines of Fortran code and 4000 lines of C code and was developed by Dr. Greg Tripoli of the University of Wisconsin. The code features a unique variable-stepped topography representation designed to handle steep slopes. It is designed to faithfully represent flows in the presence of arbitrarily rough topography while maintaining sensitivity to subtle impacts of weak topography. In this report, we give a brief description of the NMS code, followed by the initial performance rate and our optimization goal, a short discussion of our approach, an explanation of the optimization work, our final benchmark results, and finally a brief mention of what future work could be done.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2005
Accession Number
ADA435281

Entities

People

  • Chatt Williamson
  • Daniel M. Pressel
  • Dixie Hisley
  • George Petit
  • Jeffrey N. Robinson
  • Steven R. Thompson

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Compilers
  • Computer Programs
  • Computers
  • Delphi Method
  • Department Of Defense
  • Directives
  • High Performance Computing
  • Military Research
  • Operating Systems
  • Optimization
  • Parallel Computing
  • Parallel Processing
  • Simulations
  • Topography
  • Two Dimensional
  • Universities
  • Weather Forecasting

Readers

  • Atmospheric Science/Meteorology
  • Coastal Oceanography
  • Parallel and Distributed Computing.