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Energy and time constrained task scheduling on multiprocessor computers with discrete speed levels

机译:具有离散速度级别的多处理器计算机上的能源和时间受限的任务调度

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Energy and time constrained task scheduling on multiprocessor computers with discrete clock frequency and supply voltage and execution speed and power levels is addressed as combinatorial optimization problems. It is proved that the problem of minimizing schedule length with energy consumption constraint and the problem of minimizing energy consumption with schedule length constraint are NP-hard even on a uniprocessor computer with only two speed levels. A class of algorithms is developed to solve the above two problems. These algorithms include two components, namely, a list scheduling algorithm for task scheduling and a list placement algorithm for speed determination. A worst-case asymptotic performance bound and an average-case asymptotic performance bound are derived for our algorithms on uniprocessor computers, and a worst-case asymptotic performance bound is derived for our algorithms on multiprocessor computers. Extensive simulations are performed to verify our analytical results. It is found that our algorithms produce solutions very close to optimal and are practically very useful.
机译:具有离散时钟频率和电源电压以及执行速度和功率水平的多处理器计算机上受能源和时间限制的任务调度已作为组合优化问题解决。事实证明,即使在只有两个速度级别的单处理器计算机上,用能耗约束最小化调度长度的问题和用调度长度约束最小化能耗的问题也是NP难题。开发了一种算法来解决上述两个问题。这些算法包括两个部分,即用于任务调度的列表调度算法和用于速度确定的列表放置算法。在单处理器计算机上为我们的算法导出了最坏情况的渐近性能界限和平均情况下的渐近性能界限,在多处理器计算机上为我们的算法得出了最坏情况的渐近性能界限。进行了广泛的仿真以验证我们的分析结果。发现我们的算法产生的解决方案非常接近于最优,并且实际上非常有用。

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