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Algorithms 2018, 11(5), 76;

PHEFT: Pessimistic Image Processing Workflow Scheduling for DSP Clusters

Moscow Institute of Physics and Technology, Moscow 141701, Russia
Computer Science Department, CICESE Research Center, 22860 Ensenada, Baja California, Mexico
School of Electrical Engineering and Computer Science, South Ural State University, Chelyabinsk 454080, Russia
Author to whom correspondence should be addressed.
Received: 27 February 2018 / Revised: 9 April 2018 / Accepted: 9 April 2018 / Published: 22 May 2018
(This article belongs to the Special Issue Algorithms for Scheduling Problems)
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We address image processing workflow scheduling problems on a multicore digital signal processor cluster. We present an experimental study of scheduling strategies that include task labeling, prioritization, resource selection, and digital signal processor scheduling. We apply these strategies in the context of executing the Ligo and Montage applications. To provide effective guidance in choosing a good strategy, we present a joint analysis of three conflicting goals based on performance degradation. A case study is given, and experimental results demonstrate that a pessimistic scheduling approach provides the best optimization criteria trade-offs. The Pessimistic Heterogeneous Earliest Finish Time scheduling algorithm performs well in different scenarios with a variety of workloads and cluster configurations. View Full-Text
Keywords: DSP microprocessor; multicore; multiprocessors; scheduling; workflow; resource management; job allocation DSP microprocessor; multicore; multiprocessors; scheduling; workflow; resource management; job allocation

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Drozdov, A.Y.; Tchernykh, A.; Novikov, S.V.; Vladislavlev, V.E.; Rivera-Rodriguez, R. PHEFT: Pessimistic Image Processing Workflow Scheduling for DSP Clusters. Algorithms 2018, 11, 76.

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