Symbolic Analyses of Dataflow Graphs

Abstract : The synchronous dataflow model of computation is widely used to design embedded stream-processing applications under strict quality-of-service requirements (e.g., buffering size, throughput, input-output latency). The required analyses can either be performed at compile time (for design space exploration) or at run-time (for resource management and reconfigurable systems). However, these analyses have an exponential time complexity, which may cause a huge run-time overhead or make design space exploration unacceptably slow. In this paper, we argue that symbolic analyses are more appropriate since they express the system performance as a function of parameters (i.e., input and output rates, execution times). Such functions can be quickly evaluated for each different configuration or checked w.r.t. different quality-of-service requirements. We provide symbolic analyses for computing the maximal throughput of acyclic synchronous dataflow graphs, the minimum required buffers for which as soon as possible scheduling achieves this throughput, and finally the corresponding input-output latency of the graph. The paper first investigates these problems for a single parametric edge. The results are extended to general acyclic graphs using linear approximation techniques. We assess the proposed analyses experimentally on both synthetic and real benchmarks.
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Article dans une revue
ACM Transactions on Design Automation of Electronic Systems (TODAES), ACM, 2017
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https://hal.inria.fr/hal-01417146
Contributeur : Pascal Fradet <>
Soumis le : jeudi 15 décembre 2016 - 12:30:16
Dernière modification le : jeudi 15 juin 2017 - 09:08:47

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  • HAL Id : hal-01417146, version 1

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Adnan Bouakaz, Pascal Fradet, Alain Girault. Symbolic Analyses of Dataflow Graphs. ACM Transactions on Design Automation of Electronic Systems (TODAES), ACM, 2017. <hal-01417146>

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