A Rule-Based Quasi-Static Scheduling Approach for Static Islands in Dynamic Dataflow Graphs

Falk J, Zebelein C, Haubelt C, Teich J (2013)


Publication Type: Book chapter / Article in edited volumes

Publication year: 2013

Publisher: ACM

Edited Volumes: ACM Transactions on Embedded Computing Systems

City/Town: New York, NY

Book Volume: 12(3)

Pages Range: 74:1-74:31

DOI: 10.1145/2442116.2442124

Abstract

In this article, an efficient rule-based clustering algorithm for static dataflow subgraphs in a dynamic dataflow graph is presented. The clustered static dataflow actors are quasi-statically scheduled, in such a way that the global performance in terms of latency and throughput is improved compared to a dynamically scheduled execution, while avoiding the introduction of deadlocks as generated by naive static scheduling approaches. The presented clustering algorithm outperforms previously published approaches by a faster computation and more compact representation of the derived quasi-static schedule. This is achieved by a rulebased approach, which avoids an explicit enumeration of the state space. A formal proof of the correctness of the presented clustering approach is given. Experimental results show significant improvements in both, performance and code size, compared to a state-of-the-art clustering algorithm. © 2013 ACM.

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How to cite

APA:

Falk, J., Zebelein, C., Haubelt, C., & Teich, J. (2013). A Rule-Based Quasi-Static Scheduling Approach for Static Islands in Dynamic Dataflow Graphs. In ACM Transactions on Embedded Computing Systems. (pp. 74:1-74:31). New York, NY: ACM.

MLA:

Falk, Joachim, et al. "A Rule-Based Quasi-Static Scheduling Approach for Static Islands in Dynamic Dataflow Graphs." ACM Transactions on Embedded Computing Systems. New York, NY: ACM, 2013. 74:1-74:31.

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