Abstract
The performance of scientific applications in heterogeneous environments has been improved with the research advances in dynamic scheduling at application and runtime system levels. This paper presents the performance evaluation of a library as a result of an integrated approach to dynamic load balancing. This approach combines the advantages of optimising data migration via novel dynamic loop-scheduling strategies with the advances in resource management and task migration capabilities offered by a recently developed parallel runtime system. The performance of the library has been investigated by its use in three scientific applications: the N-body simulations, the profiling of automatic quadrature routines and the solution to the 3D heat equation. The investigations focus on the performance degradation owing to the overhead induced by the runtime system software layer. The experimental results obtained indicate only a slight increase in the cost of load balancing owing to this overhead. The results validate the suitability of the runtime system as an implementation platform for dynamic load-balancing schemes and underscore the significance of using the integrated approach, as well as the benefits of using the library especially in cluster applications characterised by irregular and unpredictable behaviour.
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