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Variation-aware Application Scheduling And Power Management For Chip Multiprocessors

机译:芯片多处理器的变体感知应用调度和电源管理

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Within-die process variation causes individual cores in a Chip Multiprocessor (CMP) to differ substantially in both static power consumed and maximum frequency supported. In this environment, ignoring variation effects when scheduling applications or when managing power with Dynamic Voltage and Frequency Scaling (DVFS) is suboptimal. This paper proposes variation-aware algorithms for application scheduling and power management. One such power management algorithm, called LinOpt, uses linear programming to find the best voltage and frequency levels for each of the cores in the CMP - maximizing throughput at a given power budget. In a 20-core CMP, the combination of variation-aware application scheduling and LinOpt increases the average throughput by 12-17% and reduces the average ED~2 by 30-38% - all relative to using variation-aware scheduling together with a simple extension to Intel's Foxton power management algorithm.
机译:管芯内工艺的变化会导致芯片多处理器(CMP)中的各个内核在静态功耗和支持的最大频率上都大不相同。在这种环境下,在计划应用程序或使用动态电压和频率缩放(DVFS)管理电源时,忽略变化的影响不是最佳选择。本文提出了用于应用程序调度和电源管理的变体感知算法。一种名为LinOpt的电源管理算法,使用线性编程来找到CMP中每个内核的最佳电压和频率水平-在给定的电源预算下最大化吞吐量。在20核CMP中,将变体感知的应用程序调度与LinOpt结合使用,可使平均吞吐量提高12-17%,并将平均ED〜2降低30-38%-相对于将变体感知调度与英特尔Foxton电源管理算法的简单扩展。

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