Towards an adaptive task pool implementation

Task pools can be used to achieve the dynamic load balancing that is required for an efficient parallel implementation of irregular applications. However, the performance strongly depends on a task pool implementation that is well suited for the specific application. This paper introduces an adaptive task pool implementation that enables a stepwise transition between the common strategies of central and distributed task pools. The influence of the task size on the parallel performance is investigated and it is shown that the adaptive implementation provides the flexibility to adapt to different situations. Performance results from benchmark programs and from an irregular application for anomalous diffusion simulation are presented to demonstrate the need for an adaptive strategy. It is shown that profiling information about the overhead of the task pool implementation can be used to determine an optimal task pool strategy.