Response time analysis of dataflow applications on a many-core processor with shared-memory and network-on-chip

We consider hard real-time applications running on many-core processor containing several clusters of cores linked by a Network-on-Chip (NoC). Communications are done via shared memory within a cluster and through the NoC for inter-cluster communication. We adopt the time-triggered paradigm, which is well-suited for hard real-time applications, and we consider data-flow applications, where communications are explicit. We extend the AER (Acquisition/Execution/Restitution) execution model to account for all delays and interferences linked to communications, including the interference between the NoC interface and the memory. Indeed, for NoC communications, data is first read from the initiator's local memory, then sent over the NoC, and finally written to the local memory of the target cluster. Read and write accesses to transfer data between local memories may interfere with shared-memory communication inside a cluster, and, as far as we know, previous work did not take these interferences into account. Building on previous work on deterministic network calculus and shared memory interference analysis, our method computes a static, time-triggered schedule for an application mapped on several clusters. This schedule guarantees that deadlines are met, and therefore provides a safe upper bound to the global worst-case response time.