Energy-efficiency is a critical requirement for computation-intensive real-time applications on multi-core embedded systems. Multi-core processors enable intra-task parallelism, and in this work, we study energy-efficient real-time scheduling of constrained deadline sporadic parallel tasks, where each task is represented as a directed acyclic graph (DAG). We consider a clustered multi-core platform where processors within the same cluster run at the same speed at any given time. A new concept named speed-profile is proposed to model per-task and per-cluster energy-consumption variations during run-time to minimize the expected long-term energy consumption. To our knowledge, no existing work considers energy-aware real-time scheduling of DAG tasks with constrained deadlines, nor on a clustered multi-core platform. The proposed energy-aware real-time scheduler is implemented upon an ODROID XU-3 board to evaluate and demonstrate its feasibility and practicality. To complement our system experiments in large-scale, we have also conducted simulations that demonstrate a CPU energy saving of up to 67 percent through our proposed approach compared to existing methods.

中文翻译：

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集群多核上的节能并行实时调度

能源效率是多核嵌入式系统上计算密集型实时应用程序的关键要求。多核处理器支持任务内并行性，在这项工作中，我们研究了受约束的时限偶发并行任务的节能实时调度，其中每个任务都表示为有向无环图 (DAG)。我们考虑一个集群多核平台，其中同一集群中的处理器在任何给定时间都以相同的速度运行。提出了一个名为 speed-profile 的新概念来模拟运行时每个任务和每个集群的能耗变化，以最小化预期的长期能耗。据我们所知，现有的工作都没有考虑到限期的 DAG 任务的能量感知实时调度，也没有在集群多核平台上。提议的能量感知实时调度器在 ODROID XU-3 板上实现，以评估和证明其可行性和实用性。为了补充我们的大规模系统实验，我们还进行了模拟，证明与现有方法相比，通过我们提出的方法，CPU 节能高达 67%。