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

机译:基于NoC的系统的层次结构和依赖关系的任务映射

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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.
机译:为了支持更有效的并行处理,片上网络(NoC)越来越多地被用作新的替代互连体系结构。由于NoC上的处理元件(PE)数量有限,因此在PE上高效执行应用程序任务已成为关键问题。在这项工作中,我们提出了一种层次结构且具有依赖关系的感知(HDA)任务映射,其中涵盖了空间映射和任务间依赖关系(时间)的概念,以增强任务映射的弹性。实验还表明,与现有的任务映射方法(包括首次拟合方法和基于区域的方法)相比,HDA方法可以将总处理时间分别减少多达40.79%和25.5%,并将总处理时间减少能源消耗分别高达33.16%和12.02%。

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