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Scheduling Parallel Real-Time Tasks on Virtual Processors

delete2023-01-01
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PRE
AI
X
Xu Jiang
N
Nan Guan *
Y
Yue Tang
L
Lei Qiao
W
Wang Yi
DOI:10.1109/TPDS.2022.3213024delete
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Abstract

Abstract

En 中文
In many popular parallel programming models, e.g., OpenMP (OpenMP, 2013), applications are usually dispatched into several dedicated scheduling entities (named threads in common) for which the processor time of physical platform is provided through the OS schedulers. This behavior requires for a hierarchical scheduling framework, considering each thread as a virtual processor (VP). Moreover, hierarchical scheduling allow separate applications to execute together on a common hardware platform, with each application having the illusion of executing on a dedicated component. However, the problem for scheduling parallel real-time tasks on virtual multiprocessor platform has not been addressed yet. An analogous approach to virtual scheduling for parallel real-time tasks is federeted scheudling, where each task exclusively executes on a set of dedicated physical processors. However, federated scheduling suffers significant resource wasting. In this article, we study the scheduling of real-time parallel task on virtual multiprocessors. As a physical processor is shared by virtual processors, tasks effectively share processors with each other. We conduct comprehensive performance evaluation to compare our proposed approach with existing methods of different types. Experiment results show that our approach consistently outperforms existing methods to a considerable extent under a wide range of parameter settings.
Keywords:
Real-time scheduling
vitual processors
parallel tasks
multiprocessor

Journal

IEEE Transactions on Parallel and Distributed Systems cover
IEEE Transactions on Parallel and Distributed Systems
IF:
6
Papers:
5.2K
Citations:
1.1W

Organization

C
City University of Hong Kong
Scholars:
2.3W
Papers: 3.0W
Citations: 6.1W
N
northeastern university - china
Scholars:
3.1W
Papers: 2.7W
Citations: 37
U
uppsala university
Scholars:
3.7W
Papers: 3.4W
Citations: 47
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