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Towards State-Based RT Analysis of FSM-SADFGs on MPSoCs with Shared Memory Communication

Authors: Stemmer, Ralf; Fakih, Maher; Grüttner, Kim; Nebel, Wolfgang;

Towards State-Based RT Analysis of FSM-SADFGs on MPSoCs with Shared Memory Communication

Abstract

Scenario-aware-Data-Flow Graphs (SADFGs), first intro- duced in [5], achieve a good trade-off between expressiveness (allowing the expression of more dynamic behaviors than Synchronous Data-Flow [2] graphs (SDFGs)) and analyzabil- ity. Finite-State-Machine Scenario-Aware-Data-Flow (FSM- SADF) [4] graphs are a further simplification of the general SADF graphs. Both extend SDFGs with scenarios. In an FSM- SADF MoC a set of typical scenarios are pre-defined (through a finite state machine) for a specific SDF application. The SDF application reacts to every scenario in a different manner leading to more efficiency and better throughput. In this work, we extend our previous model-checking based real-time analysis approach in [1] for the analysis of timing bounds for FSM-SADFGs mapped on a shared memory multi- core architecture (1a).

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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