Hazem had a paper entitled “Combining Dataflow Applications and Real-time Task Sets on Multi-core Platforms” accepted at the 2017 Workshop on Software and Compilers for Embedded Systems (SCOPES). This paper is a short overview of his PhD dissertation, which will be defended in Porto on May 23, and explains an approach to map and schedule a multi-/many-core system containing both applications described as traditional real-time task sets and synchronous data-flow graphs. Hazem’s approach is to convert the data-flow graph into a periodic real-time task set to unify the models before mapping, which enables him to leverage existing real-time analysis techniques and schedulers. However, converting a complex data-flow graph into a periodic task set may result in a large number of tasks, resulting in long analysis times. To mitigate this problem, he proposes a slack-based merging algorithm that allows the number of tasks to be reduced by carefully sacrificing parallelism in the data-flow graph, subject to its latency and throughput constraints. Lastly, the resulting unified real-time task set is mapped to a multi-/many-core platform interconnected by a TDM NoC using a sensitive-path-first algorithm, which first allocates tasks derived from the original data-flow graph that have the highest impact on its execution and schedulability. It is also able to exploit parallelism in graph during mapping.
We hope you enjoy the paper and wish Hazem all the best for his upcoming defense.