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VESTA: Power Modeling with Language Runtime Events

Authors:

Joseph Raskind,

Khaled Mahmoud,

Yu David LiuAuthors Info & Claims

Proceedings of the ACM on Programming Languages, Volume 8, Issue PLDI

Article No.: 172, Pages 621 - 646

https://doi.org/10.1145/3656402

Published: 20 June 2024 Publication History

Abstract

Power modeling is an essential building block for computer systems in support of energy optimization, energy profiling, and energy-aware application development. We introduce VESTA, a novel approach to modeling the power consumption of applications with one key insight: language runtime events are often correlated with a sustained level of power consumption. When compared with the established approach of power modeling based on hardware performance counters (HPCs), VESTA has the benefit of solely requiring application-scoped information and enabling a higher level of explainability, while achieving comparable or even higher precision. Through experiments performed on 37 real-world applications on the Java Virtual Machine (JVM), we find the power model built by VESTA is capable of predicting energy consumption with a mean absolute percentage error of 1.56%, while the monitoring of language runtime events incurs small performance and energy overhead.

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Cited By

Raskind JSridharan M(2024)A VM-Based Approach for Power ModelingCompanion Proceedings of the 2024 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity10.1145/3689491.3691816(7-9)Online publication date: 20-Oct-2024
https://dl.acm.org/doi/10.1145/3689491.3691816

Index Terms

VESTA: Power Modeling with Language Runtime Events
1. Hardware
  1. Power and energy
    1. Power estimation and optimization
2. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Runtime environments
  2. Software organization and properties
    1. Contextual software domains
      1. Software infrastructure
        Virtual machines

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cover image Proceedings of the ACM on Programming Languages

Proceedings of the ACM on Programming Languages Volume 8, Issue PLDI

June 2024

2198 pages

EISSN:2475-1421

DOI:10.1145/3554317

Editor:
Michael Hicks
Amazon, USA

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

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Published: 20 June 2024

Published in PACMPL Volume 8, Issue PLDI

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Cited By

Raskind JSridharan M(2024)A VM-Based Approach for Power ModelingCompanion Proceedings of the 2024 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity10.1145/3689491.3691816(7-9)Online publication date: 20-Oct-2024
https://dl.acm.org/doi/10.1145/3689491.3691816

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