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CORDIS

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

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Explainable AI for decision making - Initial (opens in new window)

A set of working examples of more context-dependent explainable AIs that allow intelligent systems to express trade-offs relevant to the current task more effectively than current approaches. An online tutorial that explains our method to enable other AI researchers to use this type of human-computer collaboration approach.

Report on communication, exploitation and dissemination - M18 (opens in new window)

Report on communication, exploitation and dissemination

Hardware accelerator architecture report (opens in new window)

Report on the detailed analysis of suitable cross-layer optimizations used to design low-power and energy-efficient hardware accelerator architectures.

Annual report on collaboration - Y1 (opens in new window)

Annual report on collaboration

Report on communication, exploitation and dissemination - Initial (opens in new window)

Report on communication, exploitation and dissemination

Task modeling from user definition results - Initial (opens in new window)

Report on ML task stage and parameter space exploration, node graph descriptions, and results in problem modeling from user descriptions.

Framework architecture, back-end, front-end design and release - Y1 (opens in new window)

Reports on the frame architecture design that integrates all software interfaces from WP1-WP4, and software release of the back-end and front-end of the framework.

Exploring new ML models Report (opens in new window)

Report on new interactive visualization methods to assist experienced and inexperienced ML developers in better understanding the design space of available ML models and in particular their relationships, benefits, and resource costs.

Publications

Adaptive Conformal Regression with Jackknife+ Rescaled Scores (opens in new window)

Author(s): Deutschmann, Nicolas; Rigotti, Mattia; Martinez, Maria Rodriguez
Published in: 2023, ISSN 0000-0000
Publisher: Transactions on Machine Learning Research, TMLR 2024
DOI: 10.48550/arxiv.2305.19901

Mixed selectivity: Cellular computations for complexity (opens in new window)

Author(s): KM Tye, EK Miller, FH Taschbach, MK Benna, M Rigotti, S Fusi
Published in: NEURON, 2024, ISSN 1097-4199
Publisher: NEURON
DOI: 10.1016/j.neuron.2024.04.017

Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging (opens in new window)

Author(s): Nicholas E. Souter, Loïc Lannelongue, Gabrielle Samuel, Chris Racey, Lincoln J. Colling, Nikhil Bhagwat, Raghavendra Selvan, Charlotte L. Rae
Published in: Imaging Neuroscience, 2023, ISSN 0270-6474
Publisher: MIT Press Direct
DOI: 10.1162/imag_a_00043

Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation (opens in new window)

Author(s): Boserup, Nicklas; Selvan, Raghavendra
Published in: Boserup , N & Selvan , R 2023 , Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation . in Proceedings of the Northern Lights Deep Learning Workshop 2023 . Septentrio Academic Publishing , Proceedings of the Northern Lights Deep Learning Workshop , vol. 4 , 2023 Northern Lights Deep Learning Workshop - NLD 2023 , Tromsø , Norway , 10/01/2023 . https://doi.org/10.7557/18.6798, 2023, ISSN 2703-6928
Publisher: Proceedings of the Northern Lights Deep Learning Workshop
DOI: 10.48550/arxiv.2208.10779

A Knowledge Distillation Framework for Multi-Organ Segmentation of Medaka Fish in Tomographic Image (opens in new window)

Author(s): Bhatt, Jwalin; Zharov, Yaroslav; Suh, Sungho; Baumbach, Tilo; Heuveline, Vincent; Lukowicz, Paul
Published in: Crossref, 2023, ISSN 1945-8452
Publisher: IEEE
DOI: 10.48550/arxiv.2302.12562

Energy-Efficient, Low-Latency and Non-contact Eye Blink Detection with Capacitive Sensing (opens in new window)

Author(s): Mengxi Liu, Sizhen Bian, Zimin Zhao, Bo Zhou, Paul Lukowicz
Published in: Frontiers in Computer Science, 2024, ISSN 1664-3224
Publisher: Frontiers
DOI: 10.3389/fcomp.2024.1394397

Operating Critical Machine Learning Models in Resource Constrained Regimes (opens in new window)

Author(s): Selvan, Raghavendra; Schön, Julian; Dam, Erik B
Published in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops ISBN: 9783031474248, 2023, ISSN 1572-8080
Publisher: Springer
DOI: 10.48550/arxiv.2303.10181

Novel adaptive quantization methodology for 8-bit floating-point DNN training. (opens in new window)

Author(s): Hassani Sadi, M., Sudarshan, C. & Wehn N.
Published in: Springer Journal of Design Automation for Embedded Systems (2023), 2024, ISSN 1572-8080
Publisher: Springer
DOI: 10.1007/s10617-024-09282-2

Energy Efficiency Impact of Processing in Memory: A Comprehensive Review of Workloads on the UPMEM Architecture (opens in new window)

Author(s): Yann Falevoz & Julien Legriel
Published in: Euro-Par 2023: Parallel Processing Workshops, 2024, ISSN 0302-9743
Publisher: Springer Cham
DOI: 10.1007/978-3-031-48803-0_13

EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search (opens in new window)

Author(s): Pedram Bakhtiarifard; Christian Igel; Raghavendra Selvan
Published in: 2024, ISSN 2379-190X
Publisher: IEEE
DOI: 10.1109/ICASSP48485.2024.10448303

Activation Compression of Graph Neural Networks Using Block-Wise Quantization with Improved Variance Minimization (opens in new window)

Author(s): Eliassen, Sebastian; Selvan, Raghavendra
Published in: Crossref, 2024, ISSN 2379-190X
Publisher: IEEE
DOI: 10.48550/arxiv.2309.11856

Probabilistic feature matching for fast scalable visual prompting

Author(s): Thomas Frick∗ , Cezary Skura∗ , Filip M. Janicki∗ , Roy Assaf , Niccolo Avogaro , Daniel Caraballo , Yagmur G. Cinar , Brown Ebouky , Ioana Giurgiu , Takayuki Katsuki , Piotr Kluska , Cristiano Malossi , Haoxiang Qiu , Tomoya Sakai , Florian Scheidegger
Published in: International Joint Conference for Artificial Intelligence (IJCAI 2024), August 2024, 2024, ISSN 0000-0000
Publisher: IJCAI

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

Author(s): Daniel Geißler, Bo Zhou, Paul Lukowicz.
Published in: International Joint Conference for Artificial Intelligence (IJCAI 2023), May 2023, 2023
Publisher: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence

CoSS: Co-optimizing Sensor and Sampling Rate for Data-Efficient AI in Human Activity Recognition (opens in new window)

Author(s): Mengxi Liu, Zimin Zhao, Daniel Geißler, Bo Zhou, Sungho Suh, Paul Lukowicz
Published in: AAAI 2024 Sustainable AI workshop, January 2024, 2024, ISSN 2331-8422
Publisher: arXiv
DOI: 10.48550/arXiv.2401.05426

The Power of Training: How Different Neural Network Setups Influence the Energy Demand (opens in new window)

Author(s): Daniel Geißler, Bo Zhou, Mengxi Liu, Sungho Suh, Paul Lukowicz
Published in: AAAI 2024 Sustainable AI workshop, January 2024, 2024, ISSN 2331-8422
Publisher: arXiv
DOI: 10.48550/arXiv.2401.01851Focustolearnmore

FieldHAR: A Fully Integrated End-to-End RTL Framework for Human Activity Recognition with Neural Networks from Heterogeneous Sensors (opens in new window)

Author(s): Mengxi Liu; Bo Zhou; Zimin Zhao; Hyeonseok Hong; Hyun Kim; Sungho Suh; Vitor Fortes Rey; Paul Lukowicz.
Published in: 2023, ISSN 2160-052X
Publisher: IEEE
DOI: 10.1109/ASAP57973.2023.00029

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