Abstract
Streaming applications are generally modelled by dataflow graphs, among which Synchronous Dataflow Graphs (SDFGs) are one of the most popular models. Self-timed Execution (STE) based methods are proved to be very powerful for analyzing and scheduling SDFGs. In this paper, an extension of STE is presented based on which, an exact algorithm is proposed to find the minimal memory usage for buffering to guarantee execution under maximal throughput (rate-optimal execution) of an SDFG on a multicore system. Experimental results show that the proposed exact algorithm obtains less buffer usage than a widely used state-of-art heuristic in a number of cases and equal buffer usage in the rest. In addition, a heuristic is proposed as an efficient approximate method, which gives equal or less buffer usage than a state-of-art heuristic.
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Ma, M., Sakellariou, R. (2016). Buffer Minimization for Rate-Optimal Scheduling of Synchronous Dataflow Graphs on Multicore Systems. In: Carretero, J., Garcia-Blas, J., Ko, R., Mueller, P., Nakano, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2016. Lecture Notes in Computer Science(), vol 10048. Springer, Cham. https://doi.org/10.1007/978-3-319-49583-5_25
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DOI: https://doi.org/10.1007/978-3-319-49583-5_25
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