Schedulability Analysis of OpenMP Applications Under Heuristic Task-To-Thread Mapping

Abstract

Task-to-thread mapping is a key process in parallel applications to achieve the best possible performance. This process is even more challenging when it is required to meet the schedulability and timing requirements of critical systems. In these systems, mapping tasks to threads is usually carried out using static scheduling (i.e., offline mapping) to improve system schedulability, with several approaches being presented in the literature. Nevertheless, there has been little analysis on the impact that these static mapping approaches have on the schedulability of applications exploiting OpenMP, a model increasingly seen as a suitable mechanism to leverage the potential of parallel and heterogeneous processor architectures. This paper, therefore, performs a throughout evaluation of the recently presented heuristic task-to-thread mapping working with different heuristics through allocation and dispatching phases, compared with state-of-the-art, in terms of schedulability. This process is performed using a state-of-the-art schedulability analysis methodology through an integration of our simulator and an existing schedulability toolset. This evaluation allows for identifying the static heuristic mapping approaches that achieve tighter schedulability analysis than other methods in the literature.