Hierarchical and Dependency-Aware Task Mapping for NoC-based Systems

To support more efficient parallel processing, Network-on-Chip (NoC) is being increasingly adopted as a new alternative interconnection architecture. With the limited number of processing elements (PEs) on an NoC, to perform application tasks efficiently on the PEs has become a key issue. In this work, we propose a hierarchical and dependency-aware (HDA) task mapping that covers the concepts of spatial mapping and inter-task dependency (temporal) to enhance the elasticity of task mapping. Experiments also show that, compared to the existing task mapping methods, including the first-fit method and the region-based method, the HDA method can reduce the total processing time by up to 40.79% and 25.5%, respectively, and reduce the total energy consumption by up to 33.16% and 12.02%, respectively.