Abstract
Static dataflow graphs enable powerful design, implementation and analysis methods for embedded systems. Nevertheless, complex signal and media processing applications—such as cognitive radio or modern video codecs—display dynamic behavior that do not fit the classical cyclo-static restrictions. An approach to tackle this limitation combines integer parameters—to express dynamic rates—with control actors—to allow topology and mode changes as well as time-dependent scheduling and constraints, as introduced in the Transaction Parameterized Dataflow (TPDF) model of computation. In this paper we present a technique to automatically analyse the static properties of a TPDF application, including consistency, liveness, boundedness and worst-case throughput. Our implementation of these analyses is validated against a set of real-life dynamic applications, demonstrating significant buffer size and throughput improvements compared to the state of the art models, including Cyclo-Static Dataflow (CSDF) and Scenario-Aware Dataflow (SADF).
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Do, X.K., Louise, S., Cohen, A. (2019). Design and Performance Analysis of Real-Time Dynamic Streaming Applications. In: Hall, M., Sundar, H. (eds) Languages and Compilers for Parallel Computing. LCPC 2018. Lecture Notes in Computer Science(), vol 11882. Springer, Cham. https://doi.org/10.1007/978-3-030-34627-0_2
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DOI: https://doi.org/10.1007/978-3-030-34627-0_2
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