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Hardware Support for Accurate Per-Task Energy Metering in Multicore Systems

机译:多核系统中精确的按任务电能计量的硬件支持

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摘要

Accurately determining the energy consumed by each task in a system will become of prominent importance in future multicore-based systems because it offers several benefits, including (i) better application energy/performance optimizations, (ii) improved energy-aware task scheduling, and (iii) energy-aware billing in data centers. Unfortunately, existing methods for energy metering in multicores fail to provide accurate energy estimates for each task when several tasks run simultaneously. This article makes a case for accurate Per-Task Energy Metering (PTEM) based on tracking the resource utilization and occupancy of each task. Different hardware implementations with different trade-offs between energy prediction accuracy and hardware-implementation complexity are proposed. Our evaluation shows that the energy consumed in a multicore by each task can be accurately measured. For a 32-core, 2-way, simultaneous multithreaded core setup, PTEM reduces the average accuracy error from more than 12% when our hardware support is not used to less than 4% when it is used. The maximum observed error for any task in the workload we used reduces from 58% down to 9% when our hardware support is used.
机译:在未来的基于多核的系统中,准确确定系统中每个任务消耗的能量将变得尤为重要,因为它具有以下优点:(i)更好的应用程序能量/性能优化,(ii)改进的能量感知任务调度,以及(iii)数据中心的能源节约计费。不幸的是,当多个任务同时运行时,现有的多核能量计量方法无法为每个任务提供准确的能量估计。本文根据跟踪每个任务的资源利用率和占用情况,为精确的按任务能源计量(PTEM)提供了依据。提出了在能量预测精度和硬件实现复杂度之间权衡不同的不同硬件实现。我们的评估表明,每个任务在多核中消耗的能量都可以准确测量。对于32核,2路,同时多线程核心设置,PTEM可以将平均精度误差从不使用我们的硬件支持时的12%以上降低到使用时的4%以下。使用硬件支持时,我们使用的工作负载中任何任务的最大观察到的错误从58%降低到9%。

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