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引用次数: 48
摘要
在嵌入式系统设计中,为了满足更高的计算能力和更低的能耗需求,具有电源管理功能的多处理器应运而生。动态电压缩放是这样一种设备,改变时钟速度和供电电压,以节省更多的能源。在本文中,我们提出ETAHM在目标多处理器系统上分配任务。为了追求全局最优解,该算法将任务调度、映射和分布式交换机利用混合在一个阶段,并结合蚁群优化算法。大量实验表明,ETAHM比CASPER (V. Kianzad et al., 2005)多节省22.71%的能源,CASPER是一种最先进的集成框架,用遗传算法来解决相同的问题。
ETAHM: An energy-aware task allocation algorithm for heterogeneous multiprocessor
In demand of more computing power and less energy use, multiprocessor with power management facility emerges in embedded system design. Dynamic voltage scaling is such a facility that varies clock speed and supply voltage to save more energy. In this paper, we propose ETAHM to allocate tasks on a target multiprocessor system. In pursuit of global optimal solution, it mixes task scheduling, mapping and DVS utilization in one phase and couples ant colony optimization algorithm. Extensive experiments show ETAHM could save 22.71% more energy than CASPER (V. Kianzad et al., 2005), a state-of-the-art integrated framework that tackles the identical problem with genetic algorithm instead.