Hard Real-Time Stationary GANG-Scheduling

Authors Niklas Ueter , Mario Günzel , Georg von der Brüggen , Jian-Jia Chen



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Author Details

Niklas Ueter
  • Department of Computer Science, TU Dortmund University, Germany
Mario Günzel
  • Department of Computer Science, TU Dortmund University, Germany
Georg von der Brüggen
  • Max Planck Institute for Software Systems, Kaiserslautern, Germany
Jian-Jia Chen
  • Department of Computer Science, TU Dortmund University, Germany

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Niklas Ueter, Mario Günzel, Georg von der Brüggen, and Jian-Jia Chen. Hard Real-Time Stationary GANG-Scheduling. In 33rd Euromicro Conference on Real-Time Systems (ECRTS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 196, pp. 10:1-10:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.ECRTS.2021.10

Abstract

The scheduling of parallel real-time tasks enables the efficient utilization of modern multiprocessor platforms for systems with real-time constrains. In this situation, the gang task model, in which each parallel sub-job has to be executed simultaneously, has shown significant performance benefits due to reduced context switches and more efficient intra-task synchronization. In this paper, we provide the first schedulability analysis for sporadic constrained-deadline gang task systems and propose a novel stationary gang scheduling algorithm. We show that the schedulability problem of gang task sets can be reduced to the uniprocessor self-suspension schedulability problem. Furthermore, we provide a class of partitioning algorithms to find a stationary gang assignment and show that it bounds the worst-case interference of each task. To demonstrate the effectiveness of our proposed approach, we evaluate it for implicit-deadline systems using randomized task sets under different settings, showing that our approach outperforms the state-of-the-art.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Concurrent algorithms
  • Computer systems organization → Embedded and cyber-physical systems
  • Computer systems organization → Real-time operating systems
Keywords
  • Real-Time Systems
  • Gang Scheduling
  • Parallel Computing
  • Scheduling Algorithms

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