DyPO : Dynamic Pareto-Optimal Configuration Selection for Heterogeneous
DyPO : Dynamic Pareto-Optimal Configuration Selection for Heterogeneous
复制标题
DyPO：异构动态帕累托最优配置选择
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
U. Ogras
中科院分区：
文献类型：
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作者：
C. A. Patil;Ganapati Bhat;P. Mishra;U. Ogras
现代多处理器片上系统（mpsoc）通过调整数千个潜在电压、频率和核心配置，提供了巨大的功率和性能优化机会。随着工作负载阶段在运行时发生变化，不同的配置可能在功率、性能或其他指标方面变得最优。由于存在大量的工作负载和配置，在运行时确定最佳配置是不可行的。本文提出了一种新的方法，可以在运行时找到作为工作负载函数的帕累托最优配置。为了实现这一点，我们执行了广泛的离线表征，以找到将性能计数器映射到最佳配置的分类器。然后，我们在运行时使用这些分类器和性能计数器来选择帕累托最优配置。我们通过最大化18个单线程和多线程应用程序的每瓦性能来评估所提出的方法。我们的实验表明，与交互式、按需和节电调控器相比，每瓦性能分别平均提高了93%、81%和6%。
Modern multiprocessor systems-on-chip (MpSoCs) offer tremendous power and performance optimization opportunities by tuning thousands of potential voltage, frequency and core configurations. As the workload phases change at runtime, different configurations may become optimal with respect to power, performance or other metrics. Identifying the optimal configuration at runtime is infeasible due to the large number of workloads and configurations. This paper proposes a novel methodology that can find the Pareto-optimal configurations at runtime as a function of the workload. To achieve this, we perform an extensive offline characterization to find classifiers that map performance counters to optimal configurations. Then, we use these classifiers and performance counters at runtime to choose Pareto-optimal configurations. We evaluate the proposed methodology by maximizing the performance per watt for 18 singleand multi-threaded applications. Our experiments demonstrate an average increase of 93%, 81% and 6% in performance per watt compared to the interactive, ondemand and powersave governors, respectively.
影响因子：
35.6
作者：
Vallina-Rodriguez, Narseo;Crowcroft, Jon
通讯作者：
Crowcroft, Jon