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Partitioning-Based Scheduling of OpenMP Task Systems With Tied Tasks
Northeastern Univ, Shenyang 110819, Peoples R China..
Northeastern Univ, Shenyang 110819, Peoples R China..
Hong Kong Polytech Univ, Hong Kong, Peoples R China..
Univ Cent Florida, Orlando, FL 32816 USA..ORCID iD: 0000-0002-5967-1058
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2021 (English)In: IEEE Transactions on Parallel and Distributed Systems, ISSN 1045-9219, E-ISSN 1558-2183, Vol. 32, no 6, p. 1322-1339Article in journal (Refereed) Published
Abstract [en]

OpenMP is a popular programming framework in both general and high-performance computing and has recently drawn much interest in embedded and real-time computing. Although the execution semantics of OpenMP are similar to the DAG task model, the constraints posed by the OpenMP specification make them significantly more challenging to analyze. A tied task is an important feature in OpenMP that must execute on the same thread throughout its entire life cycle. A previous work [1] succeeded in analyzing the real-time scheduling of tied tasks by modifying the Task Scheduling Constraints (TSCs) in OpenMP specification. In this article, we also study the real-time scheduling of OpenMP task systems with tied tasks but without changing the original TSCs. In particular, we propose a partitioning-based algorithm, P-EDF-omp, by which the tied constraint can be automatically guaranteed as long as an OpenMP task system can be successfully partitioned to a multiprocessor platform. Furthermore, we conduct comprehensive experiments with both synthetic workloads and established OpenMP benchmarks to show that our approach consistently outperforms the work in [1] -even without modifying the TSCs.

Place, publisher, year, edition, pages
IEEE COMPUTER SOC IEEE Computer Society, 2021. Vol. 32, no 6, p. 1322-1339
Keywords [en]
Multicore, parallel tasks, real-time scheduling, partitioning, OpenMP, tied tasks
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:uu:diva-437892DOI: 10.1109/TPDS.2020.3048373ISI: 000615035300001OAI: oai:DiVA.org:uu-437892DiVA, id: diva2:1538552
Available from: 2021-03-19 Created: 2021-03-19 Last updated: 2024-01-15Bibliographically approved

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Wang, Yi

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