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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Effective Task Scheduling and IP Mapping Algorithm for Heterogeneous NoC-Based MPSoC
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Effective Task Scheduling and IP Mapping Algorithm for Heterogeneous NoC-Based MPSoC

机译:基于异构NoC的MPSoC的有效任务调度和IP映射算法

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Quality of task scheduling is critical to define the network communication efficiency and the performance of the entire NoC- (Network-on-Chip-) based MPSoC (multiprocessor System-on-Chip). In this paper, the NoC-based MPSoC design process is favorably divided into two steps, that is, scheduling subtasks to processing elements (PEs) of appropriate type and quantity and then mapping these PEs onto the switching nodes of NoC topology. When the task model is improved so that it reflects better the real intertask relations, optimized particle swarm optimization (PSO) is utilized to achieve the first step with expected less task running and transfer cost as well as the least task execution time. By referring to the topology of NoC and the resultant communication diagram of the first step, the second step is done with the minimal expected network transmission delay as well as less resource consumption and even power consumption. The comparative experiments have shown the preferable resource and power consumption of the algorithm when it is actually adopted in a system design.
机译:任务调度的质量对于定义网络通信效率以及整个基于NoC-(片上网络)的MPSoC(多处理器片上系统)的性能至关重要。在本文中,基于NoC的MPSoC设计过程最好分为两个步骤,即调度子任务到适当类型和数量的处理元素(PE),然后将这些PE映射到NoC拓扑的交换节点上。当改进任务模型以更好地反映实际的任务间关系时,将使用优化的粒子群优化(PSO)来实现第一步,从而减少预期的任务运行和转移成本,并缩短任务执行时间。通过参考NoC的拓扑结构和第一步的最终通信图,可以以最小的预期网络传输延迟以及更少的资源消耗和甚至功耗来完成第二步。对比实验表明,该算法在系统设计中实际采用时,具有较好的资源和功耗。

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