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How data impacts coupled GPUs temperature prediction : a preliminary study based on synthetic data

Year: 2025

Type: conference-paper

Abstract: This paper evaluates the impact of dataset characteristics on the accuracy of temperature prediction models for coupled GPUs in Data Center (DC). Using synthetic data generated via ODEs, we compare eight data generation methods and demonstrate the data content influence prediction accuracy.

Source: IEEE/ACM International Conference on Utility and Cloud Computing (UCC)

DOI: 10.1145/3773274.3774665

Authors: Julien Beurrier, Christophe Josset, Yann Favennec, Benoît Parrein

Institutions: Centre National de la Recherche Scientifique, Laboratoire de Thermique et Energie de Nantes, Nantes Université, Institut de Recherche en Informatique et Systèmes Aléatoires, Université de Rennes

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Association Nationale de la Recherche et de la Technologie

OpenAlex ID: W7117745092

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Cites: 5

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