Publication details

S. Mazzola, G. Ara, T. Benz, B. Forsberg, T. Cucinotta, L. Benini. "Data-Driven Power Modeling and Monitoring via Hardware Performance Counter Tracking," Elsevier Journal of Systems Architecture (JSA), Vol. 167, October 2025.

Abstract

Energy-centric design is paramount in the current embedded computing era: use cases require increasingly high performance at an affordable power budget, often under real-time constraints. Hardware heterogeneity and parallelism help address the efficiency challenge, but greatly complicate online power consumption assessments, which are essential for dynamic hardware and software stack adaptations. We introduce a novel architecture-agnostic power modeling methodology with state-of-the-art accuracy, low overhead, and high responsiveness. Our methodology identifies the Performance Monitoring Counters (PMCs) with the highest linear correlation to the power consumption of each hardware sub-system, for each Dynamic Voltage and Frequency Scaling (DVFS) state. The individual, simple models are composed into a complete model that effectively describes the power consumption of the whole system, achieving high accuracy and low overhead. Our evaluation reports an average estimation error of 7.5 % for power consumption and 1.3 % for energy. We integrate these models in the Linux kernel with Runmeter, an open-source, PMC-based monitoring framework. Runmeter manages PMC sampling and processing, enabling the execution of our power models at runtime. With a worst-case time overhead of only 0.7 %, Runmeter provides responsive and accurate power measurements directly in the kernel. This information can be employed for actuation policies in workload-aware Dynamic Power Management (DPM) and power-aware, closed-loop task scheduling.

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DOI: 10.1016/j.sysarc.2025.103504

BibTeX entry:

@article{Mazzola_2025,
     title={Data-driven power modeling and monitoring via hardware performance counter tracking},
     ISSN={1383-7621},
     url={http://dx.doi.org/10.1016/j.sysarc.2025.103504},
     DOI={10.1016/j.sysarc.2025.103504},
     journal={Journal of Systems Architecture},
     publisher={Elsevier BV},
     author={Mazzola, Sergio and Ara, Gabriele and Benz, Thomas and Forsberg, Björn and Cucinotta, Tommaso and Benini, Luca},
     year={2025},
     month=jun,
     pages={103504}
}

Last updated on
11 April 2025