A rule-based static dataflow clustering algorithm for efficient embedded software synthesis
A rule-based static dataflow clustering algorithm for efficient embedded software synthesis
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一种基于规则的静态数据流聚类算法，用于高效的嵌入式软件综合
DOI：
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发表时间：
2011
期刊：
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通讯作者：
J. Teich
中科院分区：
文献类型：
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作者：
J. Falk;Christian Zebelein;C. Haubelt;J. Teich
针对嵌入到一般数据流图中的静态数据流子图，提出了一种基于广义聚类算法的高效嵌入式软件综合方法。聚集子图是准静态调度的，因此与动态调度的执行相比，在等待时间和吞吐量方面改进了合成软件的性能。与以往的算法相比，该算法具有更快的计算速度和更紧凑的准静态调度表示。这是通过基于规则的方法实现的，该方法避免了状态空间的显式枚举。实验结果表明，与最先进的聚类算法相比，在性能和代码大小方面都有显著的改进。
In this paper, an efficient embedded software synthesis approach based on a generalized clustering algorithm for static dataflow subgraphs embedded in general dataflow graphs is proposed. The clustered subgraph is quasi-statically scheduled, thus improving performance of the synthesized software in terms of latency and throughput compared to a dynamically scheduled execution. The proposed clustering algorithm outperforms previous approaches by a faster computation and a more compact representation of the derived quasi-static schedules. This is achieved by a rule-based approach, which avoids an explicit enumeration of the state space. Experimental results show significant improvements in both performance and code size when compared to a state-of-the-art clustering algorithm.