A Low Overhead Tasking Model for OpenMP

Type of publication
Article in journal
Authors

Yu, Chenle, Sara Royuela, and Eduardo Quiñones

Publisher
European Conference on Parallel Processing
Year of publication
2022
Citation

Yu, Chenle, Sara Royuela, and Eduardo Quiñones. "A Low Overhead Tasking Model for OpenMP." In European Conference on Parallel Processing, pp. 520-524. Springer, Cham, 2022.

Abstract

OpenMP is a parallel programming model widely used on shared-memory systems. Over the years, the OpenMP community tries to extend the OpenMP Specification to adapt it to modern architectures and expand its usage to other domains such as Embedded Systems. Our work focuses on improving the OpenMP tasking model by reducing the task runtime overhead. To do so, we propose a new OpenMP framework, namely, taskgraph, based on the concept of task dependency graph, where nodes are OpenMP tasks and edges describe the dependencies among them. The new framework is shown to be particularly suitable for fine-grain parallelism. It can be extended to other programming models with ease, improving the interoperability of OpenMP with different programming models, such as CUDA.