DMCA
A Rule-Based Quasi-Static Scheduling Approach for Static Islands in Dynamic Dataflow Graphs
Cached
Download Links
| Citations: | 1 - 0 self |
BibTeX
@MISC{Falk_arule-based,
author = {Joachim Falk and Christian Zebelein and Christian Haubelt and Jürgen Teich},
title = {A Rule-Based Quasi-Static Scheduling Approach for Static Islands in Dynamic Dataflow Graphs},
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
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, insucha 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.
Keyphrases
dynamic dataflow graph static island rule-based quasi-static scheduling approach presented clustering algorithm state space formal proof presented clustering approach efficient rule-based clustering algorithm derived quasi-static schedule state-of-the-art clustering algorithm significant improvement compact representation rulebased approach clustered static dataflow actor global performance static dataflow subgraphs naive static scheduling approach experimental result code size explicit enumeration
