A rule-based quasi-static scheduling approach for static islands in dynamic dataflow graphs
Author(s): Falk J, Zebelein C, Haubelt C, Teich J
Publisher: Association for Computing Machinery (ACM)
Publication year: 2013
Journal issue: 3
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.
FAU Authors / FAU Editors 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. ACM Transactions on Embedded Computing Systems, 12(3). https://dx.doi.org/10.1145/2442116.2442124
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 12.3 (2013).