2012
DOI: 10.1007/s11241-012-9166-9
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Multi-core real-time scheduling for generalized parallel task models

Abstract: 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 wit… Show more

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Cited by 141 publications
(107 citation statements)
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“…Among the list of available approaches, some remarkable work are [17], [18], [19], [20], [35], which collectively deal with the needs of some of the most popular computing paradigms. In [17] the authors considered the multi-core scenario and proposed a parallel synchronous model inspired by the primitives of OpenMPI.…”
Section: Real-time Parallel Computingmentioning
confidence: 99%
See 1 more Smart Citation
“…Among the list of available approaches, some remarkable work are [17], [18], [19], [20], [35], which collectively deal with the needs of some of the most popular computing paradigms. In [17] the authors considered the multi-core scenario and proposed a parallel synchronous model inspired by the primitives of OpenMPI.…”
Section: Real-time Parallel Computingmentioning
confidence: 99%
“…Another set of work ( [18], [19], [23], [60], [61], [62]) are related to the scheduling of parallel tasks on multi-core processors. Their computational models are mainly based on the fork-join tasks and the authors describe end-to-end interactions as a set of sequential and parallel steps.…”
Section: Real-time Parallel Computingmentioning
confidence: 99%
“…We consider part of being a global scheduling approach that there is no priority inversion within the domain: at any given time, there is never a tasklet running on a processor in the dispatching domain if there are tasklets of tasks with a higher priority (or earlier deadline) awaiting execution. This model allows for the tasklet DAG to be converted ( Figure 6) to a DAG of subtasks ( Figure 6 middle) as commonly used in the real-time systems domain [16,17,18]. Response-time analysis techniques can also be used [19,20] (restricted to non-nested tasklets), as the tasklet model is actually more restricted than the general real-time DAG model, as it considers a fully-strict fork-join, thus a synchronous model can be used [18] (Figure 6 right).…”
Section: Modelmentioning
confidence: 99%
“…The authors converted the parallel threads of a fork-join task into sequential tasks by creating a master thread, but with the difference (when compared to [5]) that no thread is ever allowed to migrate between cores. That work was generalized in [8], by allowing an arbitrary number of threads per parallel segment, and in [9] for the scheduling of tasks represented by a Directed Acyclic Graph (DAG).…”
Section: Related Workmentioning
confidence: 99%
“…Distributed systems have the particularity that the transmission delay of messages communicating threads within a task, cannot be deemed negligible as in the case of multi-core systems [5,7,8]. In here, we extend the problem of task allocation of fork-join real-time tasks presented in [1], by considering (i) a distributed multi-core architecture, and (ii) using a FTT-SE network for message transmission.…”
Section: Related Workmentioning
confidence: 99%