Communication and Shared Memory Efficient Mapping Techniques of Real-Time DAGs upon Clustered Multicore Platforms
Résumé
When it comes to mapping and scheduling Real-Time applications on parallel platforms, the Directed Acyclic Graphs (DAGs) processing model is commonly used. In this paper, we leverage the structural properties of DAG-based applications to optimize their deployment in clustered multicore processors. We assume a constant communication time between clusters and partitioned banked memory inside clusters. Our main contribution is a novel mapping (and ordering) heuristic that accounts for both communication size and DAG topology, while respecting memory constraints. Compared to the classic list scheduling-based mapping algorithm HLFET, when our approach succeeds in finding a mapping, it achieves a reduction of up to 75% in the global DAG response time and leads to better scheduling in 80% of the cases.
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