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

Information and Communications Technologies (ICT) are an increasingly important contributor to the environmental crisis. 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...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems Vol. 36; no. 1; pp. 96 - 107
Main Authors: Raffin, Guillaume, Trystram, Denis
Format: Journal Article
Language:English
Published: IEEE 01.01.2025
Institute of Electrical and Electronics Engineers
Subjects:
Central Processing Unit
Climate change
Closed box
Computer Science
Distributed, Parallel, and Cluster Computing
Energy consumption
Energy efficiency
Environmental monitoring
Global warming
Performance analysis
RAPL library (Running Average Power Limit)
Software measurement
Weather forecasting
software measurement
RAPL library (Running Average Power Limit)
energy consumption
performance analysis
energy efficiency
ISSN:1045-9219, 1558-2183
Online Access:Get full text
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Summary:Information and Communications Technologies (ICT) are an increasingly important contributor to the environmental crisis. 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 x86 processors, including 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 article, 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. We release an implementation in Rust that avoids the pitfalls we detected in existing tools, improving correctness, timing accuracy and performance, with desirable properties for monitoring and profiling parallel applications. We provide an experimental study with multiple benchmarks and processor models to evaluate the efficiency of the various mechanisms and their impact on parallel software. We 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.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2024.3492336