volume 36 issue 1 pages 96-107

Dissecting the Software-based Measurement of CPU Energy Consumption: A Comparative Analysis

Publication typeJournal Article
Publication date2025-01-01
scimago Q1
wos Q1
SJR2.097
CiteScore14.9
Impact factor6.0
ISSN10459219, 15582183, 21619883
Abstract
Every day, we experience the effects of the global warming: extreme weather events, major forest fires, storms, global warming, etc.The scientific community acknowledges that this crisis is a consequence of human activities where Information and Communications Technologies (ICT) are an increasingly important contributor.Computer scientists need tools for measuring the footprint of the code they produce and for optimizing it. Running Average Power Limit (RAPL) is a low-level interface designed by Intel that provides a measure of the energy consumption of a CPU (and more) without the need for additional hardware. Since 2017, it is available on most computing devices, including non-Intel devices such as AMD processors.More and more people are using RAPL for energy measurement, mostly like a black box without deep knowledge of its behavior.Unfortunately, this causes mistakes when implementing measurement tools.In this paper, we propose to come back to the basic mechanisms that allow to use RAPL measurements and present a critical analysis of their operations. In addition to long-established mechanisms, we explore the suitability of the recent eBPF technology (formerly and abbreviation for extended Berkeley Packet Filter) for working with RAPL.For each mechanism, we release an implementation in Rust that avoids the pitfalls we detected in existing tools, improving correctness, timing accuracy and performance. These new implementations have desirable properties for monitoring and profiling parallel applications.We also provide an experimental study with multiple benchmarks and processor models (Intel and AMD) in order to evaluate the efficiency of the various mechanisms and their impact on parallel software.These experiments show that no mechanism provides a significant performance advantage over the others. However, they differ significantly in terms of ease-of-use and resiliency.We believe that this work will help the community to develop correct, resilient and lightweight measurement tools.
Found 
Found 

Top-30

Journals

1
Future Internet
1 publication, 11.11%
Lecture Notes in Computer Science
1 publication, 11.11%
1

Publishers

1
2
3
4
Association for Computing Machinery (ACM)
4 publications, 44.44%
Institute of Electrical and Electronics Engineers (IEEE)
3 publications, 33.33%
MDPI
1 publication, 11.11%
Springer Nature
1 publication, 11.11%
1
2
3
4
  • We do not take into account publications without a DOI.
  • Statistics recalculated weekly.

Are you a researcher?

Create a profile to get free access to personal recommendations for colleagues and new articles.
Metrics
9
Share
Cite this
GOST |
Cite this
GOST Copy
Raffin G. et al. Dissecting the Software-based Measurement of CPU Energy Consumption: A Comparative Analysis // IEEE Transactions on Parallel and Distributed Systems. 2025. Vol. 36. No. 1. pp. 96-107.
GOST all authors (up to 50) Copy
Raffin G., Trystram D. Dissecting the Software-based Measurement of CPU Energy Consumption: A Comparative Analysis // IEEE Transactions on Parallel and Distributed Systems. 2025. Vol. 36. No. 1. pp. 96-107.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1109/tpds.2024.3492336
UR - https://ieeexplore.ieee.org/document/10746340/
TI - Dissecting the Software-based Measurement of CPU Energy Consumption: A Comparative Analysis
T2 - IEEE Transactions on Parallel and Distributed Systems
AU - Raffin, Guillaume
AU - Trystram, Denis
PY - 2025
DA - 2025/01/01
PB - Institute of Electrical and Electronics Engineers (IEEE)
SP - 96-107
IS - 1
VL - 36
SN - 1045-9219
SN - 1558-2183
SN - 2161-9883
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2025_Raffin,
author = {Guillaume Raffin and Denis Trystram},
title = {Dissecting the Software-based Measurement of CPU Energy Consumption: A Comparative Analysis},
journal = {IEEE Transactions on Parallel and Distributed Systems},
year = {2025},
volume = {36},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
month = {jan},
url = {https://ieeexplore.ieee.org/document/10746340/},
number = {1},
pages = {96--107},
doi = {10.1109/tpds.2024.3492336}
}
MLA
Cite this
MLA Copy
Raffin, Guillaume, et al. “Dissecting the Software-based Measurement of CPU Energy Consumption: A Comparative Analysis.” IEEE Transactions on Parallel and Distributed Systems, vol. 36, no. 1, Jan. 2025, pp. 96-107. https://ieeexplore.ieee.org/document/10746340/.