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DOI: 10.4230/LIPIcs.ECRTS.2019.7

Implementation of Memory Centric Scheduling for COTS Multi-Core Real-Time Systems

Authors: Juan M. Rivas, Joël Goossens, Xavier Poczekajlo, and Antonio Paolillo

Published in: LIPIcs, Volume 133, 31st Euromicro Conference on Real-Time Systems (ECRTS 2019)

Abstract

The demands for high performance computing with a low cost and low power consumption are driving a transition towards multi-core processors in many consumer and industrial applications. However, the adoption of multi-core processors in the domain of real-time systems faces a series of challenges that has been the focus of great research intensity during the last decade. These challenges arise in great part from the non real-time nature of the hardware arbiters that schedule the access to shared resources, such as the main memory. One solution proposed in the literature is called Memory Centric Scheduling, which defines a separate software scheduler for the sections of the tasks that will access the main memory, hence circumventing the low level unpredictable hardware arbiters. Several Memory Centric schedulers and associated theoretical analyses have been proposed, but as far as we know, no actual implementation of the required OS-level underpinnings to support dynamic event-driven Memory Centric Scheduling has been presented before. In this paper we aim to fill this gap, targeting cache based COTS multi-core systems. We will confirm via measurements the main theoretical benefits of Memory Centric Scheduling (e.g. task isolation). Furthermore, we will describe an effective schedulability analysis using concepts from distributed systems.

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Juan M. Rivas, Joël Goossens, Xavier Poczekajlo, and Antonio Paolillo. Implementation of Memory Centric Scheduling for COTS Multi-Core Real-Time Systems. In 31st Euromicro Conference on Real-Time Systems (ECRTS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 133, pp. 7:1-7:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{rivas_et_al:LIPIcs.ECRTS.2019.7,
  author =	{Rivas, Juan M. and Goossens, Jo\"{e}l and Poczekajlo, Xavier and Paolillo, Antonio},
  title =	{{Implementation of Memory Centric Scheduling for COTS Multi-Core Real-Time Systems}},
  booktitle =	{31st Euromicro Conference on Real-Time Systems (ECRTS 2019)},
  pages =	{7:1--7:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-110-8},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{133},
  editor =	{Quinton, Sophie},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2019.7},
  URN =		{urn:nbn:de:0030-drops-107448},
  doi =		{10.4230/LIPIcs.ECRTS.2019.7},
  annote =	{Keywords: real-time, multi-core, memory centric, predictability, implementation, rtos}
}

Document

DOI: 10.4230/LITES-v003-i001-a004

Optimal Scheduling of Periodic Gang Tasks

Authors: Joël Goossens and Pascal Richard

Published in: LITES, Volume 3, Issue 1 (2016). Leibniz Transactions on Embedded Systems, Volume 3, Issue 1

Abstract

The gang scheduling of parallel implicit-deadline periodic task systems upon identical multiprocessor platforms is considered. In this scheduling problem, parallel tasks use several processors simultaneously. We propose two DPFAIR (deadline partitioning) algorithms that schedule all jobs in every interval of time delimited by two subsequent deadlines. These algorithms define a static schedule pattern that is stretched at run-time in every interval of the DPFAIR schedule. The first algorithm is based on linear programming and is the first one to be proved optimal for the considered gang scheduling problem. Furthermore, it runs in polynomial time for a fixed number m of processors and an efficient implementation is fully detailed. The second algorithm is an approximation algorithm based on a fixed-priority rule that is competitive under resource augmentation analysis in order to compute an optimal schedule pattern. Precisely, its speedup factor is bounded by (2-1/m). Both algorithms are also evaluated through intensive numerical experiments.

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Joël Goossens and Pascal Richard. Optimal Scheduling of Periodic Gang Tasks. In LITES, Volume 3, Issue 1 (2016). Leibniz Transactions on Embedded Systems, Volume 3, Issue 1, pp. 04:1-04:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{goossens_et_al:LITES-v003-i001-a004,
  author =	{Goossens, Jo\"{e}l and Richard, Pascal},
  title =	{{Optimal Scheduling of Periodic Gang Tasks}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{04:1--04:18},
  ISSN =	{2199-2002},
  year =	{2016},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES-v003-i001-a004},
  doi =		{10.4230/LITES-v003-i001-a004},
  annote =	{Keywords: Real-time systems, Scheduling, Parallel tasks}
}

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Implementation of Memory Centric Scheduling for COTS Multi-Core Real-Time Systems

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Optimal Scheduling of Periodic Gang Tasks

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