Abstract
The advent of the multicore era led to the duplication of functional units through an increasing number of cores. To exploit those processors, a shared-memory parallel programming model is one possible direction. Thus, OpenMP is a good candidate to enable different paradigms: data parallelism (including loop-based directives) and control parallelism, through the notion of tasks with dependencies. But this is the programmer responsibility to ensure that data dependencies are complete such as no data races may happen. It might be complex to guarantee that no issue will occur and that all dependencies have been correctly expressed in the context of nested tasks. This paper proposes an algorithm to detect the data dependencies that might be missing on the OpenMP task clauses between tasks that have been generated by different parents. This approach is implemented inside a tool relying on the OMPT interface.
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This work was performed under the Exascale Computing Research collaboration, with the support of CEA, Intel and UVSQ.
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Bispo Vieira, R., Capra, A., Carribault, P., Jaeger, J., Pérache, M., Roussel, A. (2019). Detecting Non-sibling Dependencies in OpenMP Task-Based Applications. In: Fan, X., de Supinski, B., Sinnen, O., Giacaman, N. (eds) OpenMP: Conquering the Full Hardware Spectrum. IWOMP 2019. Lecture Notes in Computer Science(), vol 11718. Springer, Cham. https://doi.org/10.1007/978-3-030-28596-8_16
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