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Affine Data-Flow Graphs for the Synthesis of Hard Real-Time Applications

Abstract : Data-flow models ease the task of constructing feasible schedules of computations and communications of high-assurance embedded applications. One key and open issue is how to schedule data-flow graphs so as to minimize the buffering of data and reduce end-to-end latency. Most of the proposed techniques in that respect are based on either static or data-driven scheduling. This paper looks at the problem in a different way by considering priority-driven preemptive scheduling theory of periodic tasks to execute a data-flow program. Our approach to the problem can be detailed as follows. (1) We propose a model of computation in which the activation clocks of actors are related by affine functions. The affine relations describe the symbolic scheduling constraints of the data-flow graph. (2) Based on this framework, we present an algorithm that computes affine schedules in a way that minimizes buffering requirements and, in addition, guarantees the absence of overflow and underflow exceptions over communication channels. (3) Depending on the chosen scheduling policy (earliest-deadline first or rate-monotonic), we concretize the symbolic schedule by defining the period and the phase of each actor. This concretization guarantees schedulability and maximizes the processor utilization factor.
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Contributor : Thierry Gautier <>
Submitted on : Monday, December 10, 2012 - 4:27:09 PM
Last modification on : Tuesday, June 15, 2021 - 4:26:59 PM
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Adnan Bouakaz, Jean-Pierre Talpin, Jan Vitek. Affine Data-Flow Graphs for the Synthesis of Hard Real-Time Applications. Proceedings of the 2012 12th International Conference on Application of Concurrency to System Design, Jun 2012, Hamburg, Germany. pp.183-192, ⟨10.1109/ACSD.2012.16⟩. ⟨hal-00763387⟩



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