A 20-Year Retrospective on Power and Thermal Modeling and Management

Fuente: arXiv
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Autori principali: Atienza, David, Zhu, Kai, Huang, Darong, Costero, Luis
Natura: Preprint
Pubblicazione: 2025
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author Atienza, David
Zhu, Kai
Huang, Darong
Costero, Luis
author_facet Atienza, David
Zhu, Kai
Huang, Darong
Costero, Luis
contents As processor performance advances, increasing power densities and complex thermal behaviors threaten both energy efficiency and system reliability. This survey covers more than two decades of research on power and thermal modeling and management in modern processors. We start by comparing analytical, regression-based, and neural network-based techniques for power estimation, then review thermal modeling methods, including finite element, finite difference, and data-driven approaches. Next, we categorize dynamic runtime management strategies that balance performance, power consumption, and reliability. Finally, we conclude with a discussion of emerging challenges and promising research directions.
format Preprint
id arxiv_https___arxiv_org_abs_2508_05495
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A 20-Year Retrospective on Power and Thermal Modeling and Management
Atienza, David
Zhu, Kai
Huang, Darong
Costero, Luis
Systems and Control
As processor performance advances, increasing power densities and complex thermal behaviors threaten both energy efficiency and system reliability. This survey covers more than two decades of research on power and thermal modeling and management in modern processors. We start by comparing analytical, regression-based, and neural network-based techniques for power estimation, then review thermal modeling methods, including finite element, finite difference, and data-driven approaches. Next, we categorize dynamic runtime management strategies that balance performance, power consumption, and reliability. Finally, we conclude with a discussion of emerging challenges and promising research directions.
title A 20-Year Retrospective on Power and Thermal Modeling and Management
topic Systems and Control
url https://arxiv.org/abs/2508.05495