Performance analysis of weakly-consistent scenario-aware dataflow graphs

The timed dataflow model of computation is a useful performance analysis tool for Electronic System Level Design automation and embedded software synthesis. It is used to model systems, including platform mapping and resource scheduling, of components communicating and synchronizing in regular patterns. Its determinism gives it strong analysability properties and makes it less subject to state-space explosion problems. Because of its monotonic temporal behaviour it can provide hard real-time guarantees on throughput and latency. It is expressive enough to cover a fairly large class of applications and platforms. The trend however, in both embedded applications and their platforms is to become more dynamic, reaching the limits of what the model can express and analyse with tight performance guarantees. Scenario-aware dataflow (SADF) is an extension that allows more dynamism to be expressed, introducing a controlled amount of non-determinism into the model to represent different scenarios of behaviour. The combination of a relatively infrequent switching between scenarios and still deterministic dataflow behaviour within scenarios stretches the expressiveness of the model while keeping sufficient analysability. In this report we investigate so-called weakly consistent graphs in which the scenario changes are not tightly coupled with periods of repetitive behaviour of the static dataflow behaviour in scenarios as in previous methods. We define their semantics in terms of (max, +) algebra and we introduce a method to analyse throughput using a generalisation of (max, +)-automata