Time-predictable parallel programming models

Abstract

Embedded Computing (EC) systems are increas-ingly concerned with providing higher performance in real-time while HPC applications require huge amounts of information to be processed within a bounded amount of time. Addressing this convergence and mixed set of requirements needs suitable programming methodologies to exploit the massively parallel computation capabilities of the available platforms in a pre-dictable way. OpenMP has evolved to deal with the programma-bility of heterogeneous many-cores, with mature support for fine-grained task parallelism. Unfortunately, while these features are very relevant for EC heterogeneous systems, often modeled as periodic task graphs, both the OpenMP programming interface and the execution model are completely agnostic to any timing requirement that the target applications may have. The goal of our work is to enable the use of the OpenMP parallel programming model in real-time embedded systems, such that many-cores architectures can be adopted in critical real-time embedded systems. To do so, it is required to guarantee the timing behavior of OpenMP applications.