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Projekt

SustainML_EI

Application Aware, Life-Cycle Oriented Model-Hardware Co-Design Framework for Sustainable, Energy Efficient ML Systems

Application Aware, Life-Cycle Oriented Model-Hardware Co-Design Framework for Sustainable, Energy Efficient ML Systems

  • Laufzeit:

This project is based on the insight that in order to significantly reduce the CO2 footprint of ML applications power-aware applications must be as easy to develop as standard ML systems are today. Users with little or no understanding of the tradeoffs between different architecture choices and energy footprint should be able to easily reduce the power consumption of their applications.

We envision a sustainable, interactive ML framework development for Green AI that will comprehensively prioritize and advocate energy efficiency across the entire life cycle of an application and avoid AI-waste.

Partner

eProsima, INRIA, RPTU, IBM, University of Copenhagen, UpMem

Fördergeber

EU - Europäische Union

101070408

EU - Europäische Union

Projekt teilen auf:

Kontakt
Daniel Geißler, M.Sc.
Dr.-Ing. Bo Zhou

Keyfacts

Publikationen zum Projekt

The Power of Training: How Different Neural Network Setups Influence the Energy Demand

Daniel Geißler; Bo Zhou; Mengxi Liu; Sungho Suh; Paul Lukowicz

In: AAAI-24 Workshop Program. AAAI Conference on Artificial Intelligence (AAAI), Workshop Sustainable AI, AAAI Conference and Symposium Proceedings, 2024.

Zur Publikation

A Knowledge Distillation framework for Multi-Organ Segmentation of Medaka Fish in Tomographic Image

Jwalin Bhatt; Yaroslav Zharov; Sungho Suh; Tilo Baumbach; Vincent Heuveline; Paul Lukowicz

In: IEEE International Symposium on Biomedical Imaging (ISBI). IEEE International Symposium on Biomedical Imaging (ISBI-2023), April 18-21, Cartagena, Colombia, ISBN 978-1-6654-7358-3, IEEE, 4/2023.

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Latent Inspector: An Interactive Tool for Probing Neural Network Behaviors Through Arbitrary Latent Activation

Daniel Geißler; Bo Zhou; Paul Lukowicz

In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. International Joint Conference on Artificial Intelligence (IJCAI-2023), August 19-25, Macao, Macao, ISBN 978-1-956792-03-4, International Joint Conferences on Artificial Intelligence, 2023.

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