Blind identification of power sources in processors
Blind identification of power sources in processors
复制标题
处理器电源的盲识别
DOI：
10.23919/date.2017.7927274
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
A. Belouchrani
中科院分区：
文献类型：
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作者：
S. Reda;A. Belouchrani
测量功耗的能力是电源和热管理技术的核心。现代处理器配备了可以测量总功率的硬件监控机制。然而，如果需要执行细粒度的热和功率管理技术，这种集总测量是不够的。本文提出了识别多核处理器中细粒度功耗源的新方向。我们首次证明，仅通过热传感器的测量和总功耗测量就可以同时识别不同内核的功耗和芯片的热模型。我们的识别技术是盲目的，因为它不需要热模型的设计知识来识别电源。此外，我们的技术不使用性能计数器，这减少了其开销，并且与动态电压和频率缩放无缝配合。我们在基于真实多核 CPU-GPU 处理器的系统上实现了我们的技术，并且展示了仅使用总功率测量和不同工作负载下热传感器的测量来识别各个内核的运行时功耗的能力。我们还使用受控模拟环境的结果验证了我们方法的卓越准确性。
The ability to measure power consumption is at the heart of power and thermal management techniques. Modern processors are equipped with hardware monitoring mechanisms that can measure total power. However, this lumped measurement is not sufficient if there is a need to execute fine-grain thermal and power management techniques. This paper proposes a new direction for identifying the fine-grain sources of power consumption in many-core processors. For the first time, we show that it is possible to simultaneously identify both the power consumption of different cores and the thermal model of the chip from just the measurements of the thermal sensors and the total power consumption measurement. Our identification technique is blind as it does not require design knowledge of the thermal model to identify the power sources. Furthermore, our technique makes no use of the performance counters, which reduces its overhead, and works seamlessly with dynamic voltage and frequency scaling. We implement our technique on a real multi-core CPU-GPU processor-based system, and we show the ability to identify the runtime power consumption of the individual cores using just the total power measurement and the measurements of the thermal sensors under different workloads. We also verify the superior accuracy of our approach using results from a controlled simulation environment.