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Evaluation of OpenMP Dependent Tasks with the KASTORS Benchmark Suite

Philippe Virouleau 1 Pierrick Brunet 1 François Broquedis 1, 2 Nathalie Furmento 3, 4 Samuel Thibault 3 Olivier Aumage 3 Thierry Gautier 1, *
* Corresponding author
1 MOAIS - PrograMming and scheduling design fOr Applications in Interactive Simulation
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
3 RUNTIME - Efficient runtime systems for parallel architectures
CNRS - Centre National de la Recherche Scientifique : UMR5800, UB - Université de Bordeaux, Inria Bordeaux - Sud-Ouest
Abstract : The recent introduction of task dependencies in the OpenMP specifi-cation provides new ways of synchronizing tasks. Application programmers can now describe the data a task will read as input and write as output, letting the runtime system resolve fine-grain dependencies between tasks to decide which task should execute next. Such an approach should scale better than the excessive global synchronization found in most OpenMP 3.0 applications. As promising as it looks however, any new feature needs proper evaluation to encourage applica-tion programmers to embrace it. This paper introduces the KASTORS benchmark suite designed to evaluate OpenMP tasks dependencies. We modified state-of-the-art OpenMP 3.0 benchmarks and data-flow parallel linear algebra kernels to make use of tasks dependencies. Learning from this experience, we propose extensions to the current OpenMP specification to improve the expressiveness of dependen-cies. We eventually evaluate both the GCC/libGOMP and the CLANG/libIOMP implementations of OpenMP 4.0 on our KASTORS suite, demonstrating the in-terest of task dependencies compared to taskwait-based approaches.
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Submitted on : Wednesday, November 12, 2014 - 12:50:18 PM
Last modification on : Monday, December 20, 2021 - 4:50:12 PM
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Philippe Virouleau, Pierrick Brunet, François Broquedis, Nathalie Furmento, Samuel Thibault, et al.. Evaluation of OpenMP Dependent Tasks with the KASTORS Benchmark Suite. 10th International Workshop on OpenMP, IWOMP2014, Sep 2014, Salvador, Brazil. pp.16 - 29, ⟨10.1007/978-3-319-11454-5_2⟩. ⟨hal-01081974⟩



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