Abstract

Abstract—This paper proposes a modeling approach to capture the mapping of an application on a platform. The approach is based on Scenario-Aware Dataflow (SADF) models. In contrast to the related work, we express the complete design-space in a single formal SADF model. This allows us to have a compact and explorable state-space linked with an executable model capable of symbolically analyzing different mappings for their timing behavior. We can model different bindings for appli-cation tasks, different static-orders schedules for tasks bound in shared resources, as well as naturally capturing resource claiming/unclaiming using SADF semantics. Moreover, by using the inherent properties of dataflow graphs and the dynamic behavior of a Finite-State Machine, we can model different levels of pipelining, such as full application pipelining and interleaved pipelining of consecutive executions of the application. The size of the model is independent of the number of executions of the application. Since we are able to capture all this behavior in a single SADF model we can use available dataflow analysis, such as worst-case and best-case throughput and deadlock-freedom checking. Furthermore, since the model captures the design-space independently of the analysis technique, one can use different exploration approaches to analyze different sets of requirements. I.