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

Projektinformationen

SustainML

ID Finanzhilfevereinbarung: 101070408

DOI

10.3030/101070408

EK-Unterschriftsdatum 20 Juni 2022

Startdatum 1 Oktober 2022

Enddatum 30 Juni 2026

Finanziert unter

• Digital, Industry and Space

Gesamtkosten

€ 3 742 855,00

EU-Beitrag

€ 3 742 855,00

Koordiniert durch

PROYECTOS Y SISTEMAS DE MANTENIMIENTO SL
Spain

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Documents, reports (8)

Explainable AI for decision making - Initial

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

Report on communication, exploitation and dissemination

Hardware accelerator architecture report

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

Annual report on collaboration

Report on communication, exploitation and dissemination - Initial

Report on communication, exploitation and dissemination

Task modeling from user definition results - Initial

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

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

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.

Demonstrators, pilots, prototypes (1)

Carbon footprint based model optimization tool

Data Management Plan (2)

Data Management Plan - M18

Data Management Plan

Data Management Plan - Initial

Data Management Plan

Veröffentlichungen

Other (1)

Adaptive Conformal Regression with Jackknife+ Rescaled Scores

Autoren: Deutschmann, Nicolas; Rigotti, Mattia; Martinez, Maria Rodriguez
Veröffentlicht in: 2023, ISSN 0000-0000
Herausgeber: Transactions on Machine Learning Research, TMLR 2024
DOI: 10.48550/arxiv.2305.19901

Peer reviewed articles (7)

Mixed selectivity: Cellular computations for complexity

Autoren: KM Tye, EK Miller, FH Taschbach, MK Benna, M Rigotti, S Fusi
Veröffentlicht in: NEURON, 2024, ISSN 1097-4199
Herausgeber: NEURON
DOI: 10.1016/j.neuron.2024.04.017

Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging

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

Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation

Autoren: Boserup, Nicklas; Selvan, Raghavendra
Veröffentlicht 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
Herausgeber: 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

Autoren: Bhatt, Jwalin; Zharov, Yaroslav; Suh, Sungho; Baumbach, Tilo; Heuveline, Vincent; Lukowicz, Paul
Veröffentlicht in: Crossref, 2023, ISSN 1945-8452
Herausgeber: IEEE
DOI: 10.48550/arxiv.2302.12562

Energy-Efficient, Low-Latency and Non-contact Eye Blink Detection with Capacitive Sensing

Autoren: Mengxi Liu, Sizhen Bian, Zimin Zhao, Bo Zhou, Paul Lukowicz
Veröffentlicht in: Frontiers in Computer Science, 2024, ISSN 1664-3224
Herausgeber: Frontiers
DOI: 10.3389/fcomp.2024.1394397

Operating Critical Machine Learning Models in Resource Constrained Regimes

Autoren: Selvan, Raghavendra; Schön, Julian; Dam, Erik B
Veröffentlicht in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops ISBN: 9783031474248, 2023, ISSN 1572-8080
Herausgeber: Springer
DOI: 10.48550/arxiv.2303.10181

Novel adaptive quantization methodology for 8-bit floating-point DNN training.

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

Conference proceedings (8)

Energy Efficiency Impact of Processing in Memory: A Comprehensive Review of Workloads on the UPMEM Architecture

Autoren: Yann Falevoz & Julien Legriel
Veröffentlicht in: Euro-Par 2023: Parallel Processing Workshops, 2024, ISSN 0302-9743
Herausgeber: Springer Cham
DOI: 10.1007/978-3-031-48803-0_13

EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search

Autoren: Pedram Bakhtiarifard; Christian Igel; Raghavendra Selvan
Veröffentlicht in: 2024, ISSN 2379-190X
Herausgeber: IEEE
DOI: 10.1109/ICASSP48485.2024.10448303

Activation Compression of Graph Neural Networks Using Block-Wise Quantization with Improved Variance Minimization

Autoren: Eliassen, Sebastian; Selvan, Raghavendra
Veröffentlicht in: Crossref, 2024, ISSN 2379-190X
Herausgeber: IEEE
DOI: 10.48550/arxiv.2309.11856

Probabilistic feature matching for fast scalable visual prompting

Autoren: 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
Veröffentlicht in: International Joint Conference for Artificial Intelligence (IJCAI 2024), August 2024, 2024, ISSN 0000-0000
Herausgeber: IJCAI

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

Autoren: Daniel Geißler, Bo Zhou, Paul Lukowicz.
Veröffentlicht in: International Joint Conference for Artificial Intelligence (IJCAI 2023), May 2023, 2023
Herausgeber: 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

Autoren: Mengxi Liu, Zimin Zhao, Daniel Geißler, Bo Zhou, Sungho Suh, Paul Lukowicz
Veröffentlicht in: AAAI 2024 Sustainable AI workshop, January 2024, 2024, ISSN 2331-8422
Herausgeber: arXiv
DOI: 10.48550/arXiv.2401.05426

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

Autoren: Daniel Geißler, Bo Zhou, Mengxi Liu, Sungho Suh, Paul Lukowicz
Veröffentlicht in: AAAI 2024 Sustainable AI workshop, January 2024, 2024, ISSN 2331-8422
Herausgeber: 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

Autoren: Mengxi Liu; Bo Zhou; Zimin Zhao; Hyeonseok Hong; Hyun Kim; Sungho Suh; Vitor Fortes Rey; Paul Lukowicz.
Veröffentlicht in: 2023, ISSN 2160-052X
Herausgeber: IEEE
DOI: 10.1109/ASAP57973.2023.00029