Real-time scheduling and analysis of synchronous OpenMP task systems with tied tasks

Jinghao Sun, Nan Guan, Xiaoqing Wang, Chenhan Jin, Yaoyao Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)


Synchronous parallel tasks are widely used in HPC for purchasing high average performance, but merely consider how to guarantee good timing predictabilities. OpenMP is a promising framework for multi-core real-time embedded systems. The synchronous OpenMP tasks are significantly more difficult to schedule and analyze due to constraints posed by OpenMP specifications. An important OpenMP feature is tied task, which must execute on the same thread during the whole life cycle. This paper designs a novel method, called group scheduling, to schedule synchronous OpenMP tasks, which divides tasks into several groups, and assigns some of them to dedicated cores, in order to isolate tied tasks. We derive a linear-time computable response time bound. Experiments with both randomly generated and realistic OpenMP tasks show that our new bound significantly outperforms the existing bound.

Original languageEnglish
Title of host publicationProceedings of the 56th Annual Design Automation Conference 2019, DAC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
Publication statusPublished - 2 Jun 2019
Event56th Annual Design Automation Conference, DAC 2019 - Las Vegas, United States
Duration: 2 Jun 20196 Jun 2019

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Conference56th Annual Design Automation Conference, DAC 2019
Country/TerritoryUnited States
CityLas Vegas

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modelling and Simulation


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