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Title: Efficient Deterministic Federated Scheduling for Parallel Real-Time Tasks
Federated scheduling is a generalization of partitioned scheduling for parallel tasks on multiprocessors, and has been shown to be a competitive scheduling approach. However, federated scheduling may waste resources due to its dedicated allocation of processors to parallel tasks. In this work we introduce a novel algorithm for scheduling parallel tasks that require more than one processor to meet their deadlines (i.e., heavy tasks). The proposed algorithm computes a deterministic schedule for each heavy task based on its internal graph structure. It efficiently exploits the processors allocated to each task and thus reduces the number of processors required by the task. Experimental evaluation shows that our new federated scheduling algorithm significantly outperforms other state-of-the-art federated-based scheduling approaches, including semi-federated scheduling and reservation-based federated scheduling, that were developed to tackle resource waste in federated scheduling, and a stretching algorithm that also uses the tasks' graph structures.  more » « less
Award ID(s):
1814739
PAR ID:
10289282
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
2020 IEEE 26th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
Page Range / eLocation ID:
1 to 10
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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