Integrating job parallelism in real-time scheduling theory

Collette, Sébastien; Cucu, Liliana; Goossens, Joël

doi:10.1016/j.ipl.2007.11.014

Cited by 68 publications

(40 citation statements)

References 14 publications

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“…For parallel real-time tasks, most early work considered intra-task parallelism of limited task models such as malleable tasks [22,30,33] and moldable tasks [39]. Kato et al [30] studied the Gang EDF scheduling of moldable parallel task systems.…”

Section: Related Workmentioning

confidence: 99%

Analysis of Federated and Global Scheduling for Parallel Real-Time Tasks

Chen

Agrawal

et al. 2014

2014 26th Euromicro Conference on Real-Time Systems

175

119

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This paper considers the scheduling of parallel realtime tasks with implicit deadlines. Each parallel task is characterized as a general directed acyclic graph (DAG). We analyze three different real-time scheduling strategies: two well known algorithms, namely global earliestdeadline-first and global rate-monotonic, and one new algorithm, namely federated scheduling. The federated scheduling algorithm proposed in this paper is a generalization of partitioned scheduling to parallel tasks. In this strategy, each high-utilization task (utilization ≥ 1) is assigned a set of dedicated cores and the remaining low-utilization tasks share the remaining cores. We prove capacity augmentation bounds for all three schedulers. In particular, we show that if on unit-speed cores, a task set has total utilization of at most m and the criticalpath length of each task is smaller than its deadline, then federated scheduling can schedule that task set on m cores of speed 2; G-EDF can schedule it with speed 3+ √ 5 2 ≈ 2.618; and G-RM can schedule it with speed 2 + √ 3 ≈ 3.732. We also provide lower bounds on the speedup and show that the bounds are tight for federated scheduling and G-EDF when m is sufficiently large.

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Section: Related Workmentioning

confidence: 99%

Analysis of Federated and Global Scheduling for Parallel Real-Time Tasks

Chen

Agrawal

et al. 2014

2014 26th Euromicro Conference on Real-Time Systems

175

119

View full text Add to dashboard Cite

show abstract

“…Jansen [27], Lee et al [28], and Collette et al [29] study the scheduling of malleable tasks, where each task is assumed to execute on a given number of cores or processors and this number may change during execution. Manimaran et al [30] study non-preemptive EDF scheduling for moldable tasks, where the actual number of used processors is determined before starting the system and remains unchanged.…”

Section: Related Workmentioning

confidence: 99%

Multi-core Real-Time Scheduling for Generalized Parallel Task Models

Saifullah

Agrawal

et al. 2011

2011 IEEE 32nd Real-Time Systems Symposium

149

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Abstract-Multi-core processors offer a significant performance increase over single core processors. Therefore, they have the potential to enable computation-intensive real-time applications with stringent timing constraints that cannot be met on traditional single-core processors. However, most results in traditional multiprocessor real-time scheduling are limited to sequential programming models and ignore intra-task parallelism. In this paper, we address the problem of scheduling periodic parallel tasks with implicit deadlines on multi-core processors. We first consider a synchronous task model where each task consists of segments, each segment having an arbitrary number of parallel threads that synchronize at the end of the segment. We propose a new task decomposition method that decomposes each parallel task into a set of sequential tasks. We prove that our task decomposition achieves a resource augmentation bound of 4 and 5 when the decomposed tasks are scheduled using global EDF and partitioned deadline monotonic scheduling, respectively. Finally, we extend our analysis to directed acyclic graph (DAG) task model where each node in the DAG has unit execution requirement. We show how these tasks can be converted into synchronous tasks such that the same transformation can be applied and the same augmentation bounds hold.

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“…More general task models are needed that can express both the benefits and overheads of executing parts of the same task in parallel. Initial work in this area by [Collette et al 2007[Collette et al , 2008 considers the work limited job parallelism of each task defined by the rate at which it can execute on 1 to m processors. Another relevant model is the task model of [Edmonds and Pruhs 2009] which considers each task as being made up of a number of phases each of which has an amount of computation that must be completed in that phase and a speedup function indicating how the rate at which that computation is executed increases with the degree of parallelism (number of processors executing the phase).…”

Section: Open Issuesmentioning

confidence: 99%

A survey of hard real-time scheduling for multiprocessor systems

2011

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________________________________________________________________________This survey covers hard real-time scheduling algorithms and schedulability analysis techniques for homogeneous multiprocessor systems. It reviews the key results in this field from its origins in the late 1960's to the latest research published in late 2009. The survey outlines fundamental results about multiprocessor realtime scheduling that hold independent of the scheduling algorithms employed. It provides a taxonomy of the different scheduling methods, and considers the various performance metrics that can be used for comparison purposes. A detailed review is provided covering partitioned, global, and hybrid scheduling algorithms, approaches to resource sharing, and the latest results from empirical investigations. The survey identifies open issues, key research challenges and likely productive research directions.

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Integrating job parallelism in real-time scheduling theory

Cited by 68 publications

References 14 publications

Analysis of Federated and Global Scheduling for Parallel Real-Time Tasks

Analysis of Federated and Global Scheduling for Parallel Real-Time Tasks

Multi-core Real-Time Scheduling for Generalized Parallel Task Models

A survey of hard real-time scheduling for multiprocessor systems

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