Comparative Evaluation of Performance and Energy Consumption on Multi-Core Systems under CPU Frequency Governors in Native and Containerized Environments

Authors

  • Daniel L. Anunziata Universidad Nacional de Río Cuarto (UNRC), Facultad de Ingeniería — Laboratorio de Redes, Grupo de Optimización, Grupo Ciencia de Datos. Río Cuarto, Argentina. https://orcid.org/0009-0008-7954-8269
  • Emilio Corti Universidad Nacional de Río Cuarto (UNRC), Facultad de Ingeniería — Laboratorio de Redes, Grupo de Optimización, Grupo Ciencia de Datos. Río Cuarto, Argentina.

DOI:

https://doi.org/10.70567/mc.v42.ocsid8463

Keywords:

DVFS, Docker, RAPL, Sysbench, ONNX Runtime, Energy efficiency

Abstract

Energy efficiency is a strategic objective in High-Performance Computing (HPC) and in the operation of modern data centers. This work presents a study to characterize the impact of the Linux kernel’s processor frequency governors on the performance, power consumption, and thermal behavior of a multi-core architecture. The evaluation is carried out in native and containerized environments. Two workloads are analyzed: Sysbench-CPU (compute-intensive, CPU-bound) and ONNX Runtime / ResNet-50 (inference, memory-bound). The recorded metrics include latency, throughput, power, temperature, frequency, and effective CPU usage. The results show low overhead from containers and a marked influence of the frequency governor on absolute performance and energy efficiency.

References

Abraham S., Paul A.K., Khan R.I.S., y Butt A.R. On the use of containers in high performance computing environments. Future Generation Computer Systems, 117:309–321, 2021. http://doi.org/10.1109/CLOUD49709.2020.00048.

Andrae A.S.G. y Edler T. On global electricity usage of communication technology: Trends to 2030. Challenges, 6(1):117–157, 2015. http://doi.org/10.3390/challe6010117.

Anunziata D. y Corti E. Observabilidad de la eficiencia energética en servidores de centros de datos con solución de código abierto. CACIC 2024, 2024. http://doi.org/10.35537/10915/172755.

Costa G.D. y Pierson J.M. DVFS governor for HPC: Higher, faster, greener. En 2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, páginas 533–540. 2015. http://doi.org/10.1109/PDP.2015.73.

Dickson V.L. y Sebok P.T. Quantifying the power consumption of processes on linux using intel rapl. Informe Técnico, Aalborg University, 2023.

Felter W., Ferreira A., Rajamony R., y Rubio J. An updated performance comparison of virtual machines and linux containers. Informe Técnico RC25482, IBM Research, 2015.

Kopytov A. Sysbench: a system performance benchmark. https://github.com/akopytov/sysbench, 2024.

ONNX Runtime Team. Onnx runtime: High-performance inference engine. https://onnxruntime.ai, 2024. Official documentation.

Potdar A.M., GB N.D., Kengond S., y Mulla M.M. Performance evaluation of docker container and virtual machine. Procedia Computer Science, 171:1419–1428, 2020. http://doi.org/10.1016/j.procs.2020.04.152.

Raffin G. y Trystram D. Dissecting the software-based measurement of cpu energy consumption: A comparative analysis. IEEE Transactions on Parallel and Distributed Systems, 36(1):96–107, 2025. http://doi.org/10.1109/TPDS.2024.3492336.

Santos E.A., McLean C., Solinas C., y Hindle A. How does docker affect energy consumption? evaluating workloads in and out of docker containers. Journal of Systems and Software, 146:14–25, 2018. ISSN 0164-1212. http://doi.org/https://doi.org/10.1016/j.jss.2018.07.077.

Selim S., Chang Y., yWang Y. Hardware for hpc, data centers, and ai 2025–2035: Technologies, markets, forecasts. IDTechEx Report, 2025. https://www.idtechex.com/en/research-report/hardware-for-hpc-and-ai-2025/1058.

Zhao Y., He R., Kersting N., Liu C., Agrawal S., Chetia C., y Gu Y. Onnxexplainer: an onnx based generic framework to explain neural networks using shapley values. 2023. http://doi.org/10.48550/arXiv.2309.16916.

Zhou N., Zhou H., y Hoppe D. Containerization for high performance computing systems: Survey and prospects. IEEE Transactions on Software Engineering, 49(4):2722–2740, 2023. http://doi.org/10.1109/TSE.2022.3229221.

Downloads

Published

2025-12-05

Issue

Vol. 42 No. 15 (2025): High Performance Computing

Section

Conference Papers in MECOM 2025

License

Copyright (c) 2025 Argentine Association for Computational Mechanics

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

This publication is open access diamond, with no cost to authors or readers.

Only those papers that have been accepted for publication and have been presented at the AMCA congress will be published.