ISCAS OpenIR
Memory-constrained static rate-optimal scheduling of synchronous dataflow graphs via retiming
Zhu, Xue-Yang (1); Geilen, Marc (2); Basten, Twan (2); Stuijk, Sander (2)
2014
Conference Name17th Design, Automation and Test in Europe, DATE 2014
Conference DateMarch 24, 2014 - March 28, 2014
Conference PlaceDresden, Germany
Indexed TypeEI
Publish PlaceInstitute of Electrical and Electronics Engineers Inc.
ISSN15301591
ISBN9783981537024
Department(1) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (2) Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
English AbstractSynchronous dataflow graphs (SDFGs) are widely used to model digital signal processing (DSP) and streaming media applications. In this paper, we use retiming to optimize SDFGs to achieve a high throughput with low storage requirement. Using a memory constraint as an additional enabling condition, we define a memory constrained self-timed execution of an SDFG. Exploring the state-space generated by the execution, we can check whether a retiming exists that leads to a rate-optimal schedule under the memory constraint. Combining this with a binary search strategy, we present a heuristic method to find a proper retiming and a static scheduling which schedules the retimed SDFG with optimal rate (i.e., maximal throughput) and with as little storage space as possible. Our experiments are carried out on hundreds of synthetic SDFGs and several models of real applications. Differential synthetic graph results and real application results show that, in 79% of the tested models, our method leads to a retimed SDFG whose rate-optimal schedule requires less storage space than the proven minimal storage requirement of the original graph, and in 20% of the cases, the returned storage requirements equal the minimal ones. The average improvement is about 7.3%. The results also show that our method is computationally efficient. © 2014 EDAA.; Synchronous dataflow graphs (SDFGs) are widely used to model digital signal processing (DSP) and streaming media applications. In this paper, we use retiming to optimize SDFGs to achieve a high throughput with low storage requirement. Using a memory constraint as an additional enabling condition, we define a memory constrained self-timed execution of an SDFG. Exploring the state-space generated by the execution, we can check whether a retiming exists that leads to a rate-optimal schedule under the memory constraint. Combining this with a binary search strategy, we present a heuristic method to find a proper retiming and a static scheduling which schedules the retimed SDFG with optimal rate (i.e., maximal throughput) and with as little storage space as possible. Our experiments are carried out on hundreds of synthetic SDFGs and several models of real applications. Differential synthetic graph results and real application results show that, in 79% of the tested models, our method leads to a retimed SDFG whose rate-optimal schedule requires less storage space than the proven minimal storage requirement of the original graph, and in 20% of the cases, the returned storage requirements equal the minimal ones. The average improvement is about 7.3%. The results also show that our method is computationally efficient. © 2014 EDAA.
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/16604
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Zhu, Xue-Yang ,Geilen, Marc ,Basten, Twan ,et al. Memory-constrained static rate-optimal scheduling of synchronous dataflow graphs via retiming[C]. Institute of Electrical and Electronics Engineers Inc.,2014.
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