A multi-threaded programming strategy for parallel Weather Forecast Model using C#

Abstract

It is seen that Weather Forecast Models (WFMs) are often implemented using the sequential programs. This usually takes longer execution time, larger computer resources and more power as WFMs involve high level computational tasks to process large amount of weather forecast data. These become problems for the weather forecast companies in terms of WFM performance. The companies have already tried to use the multi-core systems to overcome these, but it does not work always because of the poor selection and implementation of programming strategies. By addressing these problems, a research project has been conducted as a case study for the weather production company named Weather2 Ltd. The case study attempted multi-threaded programming based on the multi-core systems as a different implementation strategy for Weather2's WFM as solution to their problems in using sequential programs. The results of the case study showed that this new strategy could improve the performance of WFM significantly by reducing the execution time, using less computer resources and power. This paper presents the case study and its results. © 2012 IEEE.