Symbolic analysis of dataflow applications mapped onto shared heterogeneous resources

Embedded streaming applications require design-time temporal analysis to verify real-time constraints such as throughput and latency. In this paper, we introduce a new analytical technique to compute temporal bounds of streaming applications mapped onto a shared multiprocessor platform. We use an expressively rich application model that supports adaptive applications where graph structure, execution times and data rates may change dynamically. The analysis technique combines symbolic simulation in (max; +) algebra with worst-case resource availability curves. It further enables a tighter performance guarantee by improving the WCRTs of service requests that arrive in the same busy time. Evaluation on real-life application graphs shows that the technique is tens of times faster than the state-of-the-art and enables tighter throughput guarantees, up to a factor of 4, compared to the typical worst-case analysis.