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A task allocation method for heterogeneous multi-core system based on genetic algorithm

机译:基于遗传算法的异构多核系统任务分配方法

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摘要

Heterogeneous multi-core platforms are increasingly prevalent due to perceived superior performance over homogeneous systems. In order to maximize performance, each task needs to be mapped to the most appropriate processor. This paper implements a task allocation method based on genetic algorithm. The genetic algorithm is used to sample the application load feature in the task scheduling time slice, and its complicated iterative process is distributed to the following multiple scheduling sampling periods to select the core which complies with its calculation characteristic for each task. Experimental results demonstrate that the algorithm can effectively improve the system performance, compared with the built-in task scheduling mechanism of Linux 2.6 kernel.
机译:由于在均匀系统中感知,异构多核平台越来越普遍。为了最大化性能,每个任务都需要映射到最合适的处理器。本文实现了基于遗传算法的任务分配方法。遗传算法用于对任务调度时间片中的应用加载特征进行采样,其复杂的迭代过程分布到以下多个调度采样周期,以选择符合每个任务的计算特性的核心。实验结果表明,与Linux 2.6内核的内置任务调度机制相比,该算法可以有效地提高系统性能。

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