Dynamic Component Extension: a Strategy for Performance Improvement in Multicomponent Applications

Abstract

Multicomponent application paradigms have gained prominence in many significant multidisciplinary scientific applications. In this work, we propose a software strategy called dynamic component extension for multicomponent applications to improve application performance by minimizing processor idling. In this strategy, the processor space of a component is dynamically extended to include the processors of other components during certain computationally intensive phases of the component. We demonstrate its use in improving the performance of one of the most prominent multicomponent applications, the community climate system model (CCSM). In this application, we dynamically extend the atmosphere component to minimize the idling in other components caused by large periodic temporal load imbalances in the atmosphere component. By means of experiments on different parallel platforms with different numbers of processors, we show that using our strategy can lead to about 15% reduction and savings of several days in execution times of CCSM for 1000-year simulation runs.