IoT devices, edge devices and embedded devices, in general, are ubiquitous. The energy consumption of such devices is important both due to the total number of devices deployed and because such devices are often battery-powered. Hence, improving the energy efficiency of such high-performance embedded systems is crucial. The first step to decreasing energy consumption is to accurately measure it, as we base our conclusions and decisions on the measurements. Given the importance of the measurements, it surprised us that most publications dedicate little space and effort to the description of their experimental setup. One variable of importance of the measurement system is the sampling frequency, e.g. how often the continuous signal's voltage and current are measured per second. In this paper, we systematically explore the impact of the sampling frequency on the accuracy of the measurement system. We measure the energy consumption of a Hardkernel Odroid-XU4 board executing nine Rodinia benchmarks with a wide range of runtimes and options at 4kHz, which is the standard sampling frequency of our measurement system. We show that one needs to measure at least at 350Hz to achieve equivalent results in comparison to the original power traces. Sampling at 1Hz (e.g. Hardkernel SmartPower2) results in a maximum error of 80%.
翻译:一般而言,IoT装置、边缘装置和嵌入装置无处不在,这种装置的能量消耗很重要,因为所部署装置的总数很大,而且这种装置往往是电池动力装置。因此,提高这种高性能嵌入系统的能源效率至关重要。降低能源消耗的第一步是准确测量能源消耗,因为我们根据测量结果和决定来计算能源消耗。鉴于测量的重要性,我们惊讶地看到,大多数出版物很少用空间和精力来描述其实验设置。测量系统的一个重要变量是取样频率,例如连续信号的电压和电流每秒测量一次的频率。在本文件中,我们系统地探讨取样频率对测量系统的准确性的影响。我们测量Hardkernel Odroid-XU4 板的能源消耗量,在4kHz执行9个范围广泛的运行时间和选项基准,这是我们测量系统的标准采样频率。我们显示,至少需要测量350Hz的频率,才能达到与80-Hz最大原始电压级结果相比的相等的结果。 Sampl2,在智能 HRaldal-hal 18 的硬度中,需要至少测量到350Hz。