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Cited by 298Parallel Computing and Optimization TechniquesEnergy Efficiency in ComputingCloud Computing and Resource Management

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RAPL in Action: Experiences in Using RAPL for Power Measurements

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Khan, Kashif Nizam, Hirki, Mikael, Niemi, Tapio, Nurminen, Jukka K., Ou, Zhonghong·2018·ACM Transactions on Modeling and Performance Evaluation of Computing Systems
DOI 10.1145/3177754
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Abstract

To improve energy efficiency and comply with the power budgets, it is important to be able to measure the power consumption of cloud computing servers. Intel’s Running Average Power Limit (RAPL) interface is a powerful tool for this purpose. RAPL provides power limiting features and accurate energy readings for CPUs and DRAM, which are easily accessible through different interfaces on large distributed computing systems. Since its introduction, RAPL has been used extensively in power measurement and modeling. However, the advantages and disadvantages of RAPL have not been well investigated yet. To fill this gap, we conduct a series of experiments to disclose the underlying strengths and weaknesses of the RAPL interface by using both customized microbenchmarks and three well-known application level benchmarks: Stream , Stress-ng , and ParFullCMS . Moreover, to make the analysis as realistic as possible, we leverage two production-level power measurement datasets from the Taito , a supercomputing cluster of the Finnish Center of Scientific Computing and also replicate our experiments on Amazon EC2. Our results illustrate different aspects of RAPL and document the findings through comprehensive analysis. Our observations reveal that RAPL readings are highly correlated with plug power, promisingly accurate enough, and have negligible performance overhead. Experimental results suggest RAPL can be a very useful tool to measure and monitor the energy consumption of servers without d…

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Metadata

Authors
Khan, K. N., Hirki, M., Niemi, T., Nurminen, J. K., & Ou, Z.
Affiliations
  • Helsinki Institute of Physics (FI)
  • Beijing University of Posts and Telecommunications (CN)
ORCID
Venue
ACM Transactions on Modeling and Performance Evaluation of Computing Systems
Publisher
Association for Computing Machinery (ACM)
Published
2018-03-22
Volume
3
Issue
2
Pages
1-26
ISSN
  • 2376-3639 (ISSN-L)
  • 2376-3647
DOI
10.1145/3177754
OpenAlex
W2793320545
Cited by
298
References
35
Citations by year
2026: 61 · 2025: 78 · 2024: 52 · 2023: 31 · 2022: 22 · 2021: 21 · 2020: 16 · 2019: 16 · 2018: 1
FWCI
15.49
Type
journal article
Language
en
Open access
Licence
Locations
  • ACM Transactions on Modeling and Performance Evaluation of Computing Systems (publishedVersion)
  • Työväentutkimus Vuosikirja (submittedVersion, other-oa)
  • IRIS (submittedVersion)
  • SERVAL (Université de Lausanne) (submittedVersion)
Funders
Central Universities and National Natural Science Foundation of China (61702046)
Topics
  • Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
  • Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
  • Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
Keywords
RAPL, power measurement, energy efficiency, processor power consumption, Plug Power, power budgeting, power monitoring, performance overhead, driver support, Amazon EC2

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CoChat. (2026). Citation check: RAPL in Action: Experiences in Using RAPL for Power Measurements. https://app.cochat.ai/papers/10.1145/3177754
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Khan, K. N., Hirki, M., Niemi, T., Nurminen, J. K., & Ou, Z. (2018). RAPL in Action: Experiences in Using RAPL for Power Measurements. ACM Transactions on Modeling and Performance Evaluation of Computing Systems. https://doi.org/10.1145/3177754