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CORDIS - Resultados de investigaciones de la UE
CORDIS

Device-Edge-Cloud Intelligent Collaboration framEwork

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Implementation Report of CI/CD Environment (se abrirá en una nueva ventana)

Technical description of the selected CI/CD environment including the chosen code quality and security tools. This further includes the description of the configuration of quality gates preventing poor quality or insecure code from being built.

Use Case Requirements (se abrirá en una nueva ventana)

A list of the selected use cases and a detailed inventory of requirements for each application use case of the DECICE framework that covers hardware specifications (e.g. networking, storage, computinge) and performance demands.

Specification of the Optimization Scope (se abrirá en una nueva ventana)

A detailed technical description of the system characteristics and metrics necessary for the scheduler and the supported user-requirements for job/workload.

AI-Scheduler Prototypes for Storage and Compute (se abrirá en una nueva ventana)

Individual prototypes of the two AI-schedulers for storage and compute are implemented and are ready for use in the synthetic training environment.

Dissemination & Communication Plan (se abrirá en una nueva ventana)

This deliverable will be focused on informing the broad audience on the project’s goals and activities, and raising awareness on its results. To achieve this, DECICE will lay out the target stakeholders as well as the means to reach them.  This will be updated in M18 for adjusting the plan to the requirements of the project and new opportunities and challenges. The plan will lay out the various activities which will seek to encourage stakeholders to use and uptake the AI-techniques and models developed by the project for further research or commercial activities.

Integration of Monitoring Framework (se abrirá en una nueva ventana)

This deliverable contains the software components, technical descriptions and documentation for the monitoring framework.

Project Handbook (se abrirá en una nueva ventana)

This document provides an overview of management and administrative procedures that are in place to guarantee the quality of project results and efficient teamwork. Key aspects of these procedures and standards are discussed and agreed upon during the kick-off general assembly. This includes a description of the collaborative environment, how to organize material, a FAQ for typical questions of project partners, and plans for quality assurance, technical integration, risk management, communication and dissemination. For example, the QA and risk management plan defines guidelines, procedures, and checklists to be followed for project specific documentation, criteria for the reviews, communication, innovation potential, progress and impact indicators, and contingency plans. The plan also includes assigned deliverable and milestone review teams and documents the potential and emerged risks. Throughout the project, the project handbook will be constantly updated.

Development Environment Specification (se abrirá en una nueva ventana)

A detailed technical specification of the necessary hardware and software to create a development environment for the DECICE framework as well as the definition of performance metrics for evaluation.

Online and Media Presence (se abrirá en una nueva ventana)

This deliverable will present information on the development of the project website, the utilized social media channels and project newsletter.

Data Management Plan (se abrirá en una nueva ventana)

The first version of the DMP is based on the Horizon Europe guidelines. It ensures that created data and research results are findable, accessible, interoperable and reusable (FAIR). It covers the handling of data during and after the project: the generated, collected and processed data, the procedures and standards applied, the restrictions on data, and the data curation and preservation. The DMP will be periodically updated similarly to the project handbook.

Project Development Environment Deployed for Phase 1 and 2 (se abrirá en una nueva ventana)

A project development environment is deployed for Phase 1 (one site) and Phase 2 (2 sites) with access for all project members to enable performance evaluations.

Synthetic Test Environment (se abrirá en una nueva ventana)

This deliverable contains the code and documentation for the synthetic test environment as defined in T3.5 that allows the training of the ML-models from WP2. Slight adaptations may be necessary after the initial version while the overall system architecture is not yet finalized. It also contains a description of the architecture.

Digital Twin (se abrirá en una nueva ventana)

Core of this deliverable is the implementation of the digital twin and the corresponding interfaces, including the integration of the Telemetry API and the interface to the AI-schedulers.

Publicaciones

GRAAFE: GRaph Anomaly Anticipation Framework for Exascale HPC systems (se abrirá en una nueva ventana)

Autores: Martin Molan, Mohsen Seyedkazemi Ardebili, Junaid Ahmed Khan, Francesco Beneventi, Daniele Cesarini, Andrea Borghesi, Andrea Bartolini
Publicado en: Future Generation Computer Systems, Edición 160, 2024, ISSN 0167-739X
Editor: Elsevier BV
DOI: 10.1016/J.FUTURE.2024.06.032

The REGALE Library: A DDS Interoperability Layer for the HPC PowerStack (se abrirá en una nueva ventana)

Autores: Giacomo Madella, Federico Tesser, Lluis Alonso, Julita Corbalan, Daniele Cesarini, Andrea Bartolini
Publicado en: Journal of Low Power Electronics and Applications, Edición 15, 2025, ISSN 2079-9268
Editor: MDPI AG
DOI: 10.3390/JLPEA15010010

Performance Characterization of Hardware/Software Communication Interfaces in End-to-End Power Management Solutions of High-Performance Computing Processors (se abrirá en una nueva ventana)

Autores: Antonio del Vecchio, Alessandro Ottaviano, Giovanni Bambini, Andrea Acquaviva, Andrea Bartolini
Publicado en: Energies, Edición 17, 2025, ISSN 1996-1073
Editor: MDPI AG
DOI: 10.3390/EN17225778

Directly-trained Spiking Neural Networks for Deep Reinforcement Learning: Energy efficient implementation of event-based obstacle avoidance on a neuromorphic accelerator (se abrirá en una nueva ventana)

Autores: Luca Zanatta, Alfio Di Mauro, Francesco Barchi, Andrea Bartolini, Luca Benini, Andrea Acquaviva
Publicado en: Neurocomputing, Edición 562, 2025, ISSN 0925-2312
Editor: Elsevier BV
DOI: 10.1016/J.NEUCOM.2023.126885

M100 ExaData: a data collection campaign on the CINECA’s Marconi100 Tier-0 supercomputer (se abrirá en una nueva ventana)

Autores: Borghesi, Andrea; Di Santi, Carmine; Molan, Martin; Seyedkazemi Ardebili, Mohsen; Mauri, Alessio; Guarrasi, Massimiliano; Galetti, Daniela; Cestari, Mirko; Barchi, Francesco; BENINI, LUCA; Beneventi, Francesco; Bartolini, Andrea
Publicado en: Scientific Data, Vol 10, Iss 1, Pp 1-10 (2023), 2023, ISSN 2052-4463
Editor: Nature
DOI: 10.3929/ethz-b-000614369

Fair and efficient resource allocation via vehicle-edge cooperation in 5G-V2X networks (se abrirá en una nueva ventana)

Autores: Muhammed Nur Avcil, Mujdat Soyturk, Burak Kantarci
Publicado en: Vehicular Communications, Edición 48, 2024, ISSN 2214-2096
Editor: Elsevier BV
DOI: 10.1016/J.VEHCOM.2024.100773

HazardNet: A thermal hazard prediction framework for datacenters (se abrirá en una nueva ventana)

Autores: Seyedkazemi Ardebili, Mohsen, Andrea Acquaviva, Luca Benini, and Andrea Bartolini.
Publicado en: Future Generation Computer Systems, ISSN 1872-7115
Editor: ScienceDirect
DOI: 10.1016/J.FUTURE.2024.01.031

PM100: A Job Power Consumption Dataset of a Large-scale Production HPC System (se abrirá en una nueva ventana)

Autores: Francesco Antici, Mohsen Seyedkazemi Ardebili, Andrea Bartolini, Zeynep Kiziltan
Publicado en: Proceedings of the SC '23 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, 2025
Editor: ACM
DOI: 10.1145/3624062.3624263

DECICE (se abrirá en una nueva ventana)

Autores: Julian Martin Kunkel; Christian Boehme; Jonathan Decker; Fabrizio Magugliani; Dirk Pleiter; Bastian Koller; Karthee Sivalingam; Sabri Pllana; Alexander Nikolov; Mujdat Soyturk; Christian Racca; Andrea Bartolini; Adrian Tate; Berkay Yaman
Publicado en: Crossref, 2023, ISBN 9798400701405
Editor: Association for Computing Machinery
DOI: 10.48550/arxiv.2305.02697

SpikeStream: Accelerating Spiking Neural Network Inference on RISC-V Clusters with Sparse Computation Extensions (se abrirá en una nueva ventana)

Autores: Simone Manoni, Paul Scheffler, Luca Zanatta, Andrea Acquaviva, Luca Benini, Andrea Bartolini
Publicado en: 2025 Design, Automation & Test in Europe Conference (DATE), 2025
Editor: IEEE
DOI: 10.23919/DATE64628.2025.10992749

TinyLid: a RISC-V accelerated Neural Network For LiDAR Contaminant Classification in Autonomous Vehicle (se abrirá en una nueva ventana)

Autores: Grafika Jati, Martin Molan, Francesco Barchi, Andrea Bartolini, Andrea Acquaviva
Publicado en: Proceedings of the 21st ACM International Conference on Computing Frontiers, 2025
Editor: ACM
DOI: 10.1145/3649153.3649201

Comparing Fault-tolerance in Kubernetes and Slurm in HPC Infrastructure

Autores: Mirac Aydin, Michael Bidollahkhani, and Julian M. Kunkel
Publicado en: ISSN 2308-4499
Editor: ADVCOMP 2024

Graph Neural Networks for Anomaly Anticipation in HPC Systems (se abrirá en una nueva ventana)

Autores: Martin Molan, Junaid Ahmed Khan, Andrea Borghesi, Andrea Bartolini
Publicado en: Companion of the 2023 ACM/SPEC International Conference on Performance Engineering, 2025
Editor: ACM
DOI: 10.1145/3578245.3585335

Bio-Inspired Drone Control: A Reinforcement Learning-Trained Spiking Neural Networks for Agile Navigation in Dynamic Environment (se abrirá en una nueva ventana)

Autores: Yin-Ching Lee, Sebastiano Mengozzi, Luca Zanatta, Andrea Bartolini, Andrea Acquaviva, Francesco Barchi
Publicado en: 2025 IEEE International Conference on Omni-layer Intelligent Systems (COINS), 2025
Editor: IEEE
DOI: 10.1109/COINS65080.2025.11125776

HOSHMAND: Accelerated AI-Driven Scheduler Emulating Conventional Task Distribution Techniques for Cloud Workloads

Autores: Michael Bidollahkhani, Aasish Kumar Sharma and Julian Martin Kunkel
Publicado en: Edición CFP24061-ART, ISSN 2836-3795
Editor: IEEE COMPSAC

Towards Nano-Drones Agile Flight Using Deep Reinforcement Learning (se abrirá en una nueva ventana)

Autores: Sebastiano Mengozzi, Luca Zanatta, Francesco Barchi, Andrea Bartolini, Andrea Acquaviva
Publicado en: 2024 IEEE International Conference on Omni-layer Intelligent Systems (COINS), 2024
Editor: IEEE
DOI: 10.1109/COINS61597.2024.10622558

Monte Cimone v2: Down the Road of RISC-V High-Performance Computers

Editor: Emanuele Venieri, Simone Manoni, Gabriele Ceccolini, Giacomo Madella, Federico Ficarelli, Daniele Gregori, Daniele Cesarini, Luca Benini, Andrea Bartolini

https://arxiv.org/html/2504.01972

Autores: Umberto Laghi, Simone Manoni, Emanuele Parisi, Andrea Bartolini
Publicado en: 2025
Editor: arxiv.org

MCBound: An Online Framework to Characterize and Classify Memory/Compute-bound HPC Jobs

Autores: Antici, Francesco ; Bartolini, Andrea ; Kiziltan, Zeynep ; Babaoglu, Ozalp ; Kodama, Yuetsu
Publicado en: 2024
Editor: Universtià di Bologna

Assessing Tenstorrent’s RISC-V MatMul Acceleration Capabilities

Autores: Hiari Pizzini Cavagna, Daniele Cesarini, Andrea Bartolini
Publicado en: 2025
Editor: Cornell University

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