Projects

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Slices Implementation Phase (SLICES IP)

The digital infrastructures research community continues to face numerous new challenges towards the design of the Next Generation Internet. This is an extremely complex ecosystem encompassing communication, networking, data management and data intelligence issues, supported by established and emerging technologies such as IoT, 5G/6G, cloud-to-edge computing. Coupled with the enormous amount of data generated and exchanged over the network, this calls for incremental and radically new infrastructure design paradigms. Experimentally driven research is becoming worldwide a standard, which has to be supported by large-scale research infrastructures to make results trusted, repeatable and accessible to the research communities. SLICES-RI (Research Infrastructure), which has been included in the 2021 ESFRI Roadmap, aims to answer these problems by building a large infrastructure needed for the experimental research on various aspects of the continuum IoT-edge-Cloud. It will provide the necessary resources to continuously design, experiment, operate and automate the full lifecycle management of digital infrastructures, data, applications, and services. Based on the three preceeding projects within SLICES-RI, SLICES-DS (Design Study), SLICES-SC (Starting Community) and SLICES-PP (Preparatory Phase), the SLICES-IP project will validate the requirements to engage in the operation phase of the RI lifecycle. It will complete the last step towards the creation of an ERIC as legal structure, strengthen the actions to engage more Member States and other stakeholders, secure their commitment and funding needed for the platform to operate. SLICES-IP will lead the definition of the implementation of the final architecture and common services. It will position SLICES as an impactful instrument to support advanced European research, industrial competitiveness and societal impact in the digital era.

Project Information

  • URL: http://slices-ri.eu/
  • Topic: HORIZON-INFRA-2025-01-DEV-02
  • Starting date: 2026, June 1st
  • End date: 2029, May 31th
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ODISSEE: Online Data Intensive Solutions for Science in the Exabytes Era

Research sectors such as high-energy physics and astronomy offer critical insights that have the potential to revolutionise research and development, leading to breakthroughs in theoretical fields. However, these areas often require intensive research, expensive tools, and substantial long-term funding, without which their results may be limited. The EU-funded ODISSEE project will bring together the efforts of three pan-European ESFRI infrastructures in the physical sciences, alongside several other key sectors, to enhance European excellence and leadership in astronomy and high-energy physics. The project will provide access to essential high-quality hardware, software, R&D programmes and state-of-the-art experimental facilities to support key scientific projects and researchers, particularly those focused on the search for dark matter.

Project Information

  • URL: CORDIS web site
  • Starting date: 2025, January 1st
  • End date: 2027, December 31th

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Exa-SofT : HPC software and tools

A NumPEx PEPR project

Though significant efforts have been devoted to the implementation and optimization of several crucial parts of a typical HPC software stack, most HPC experts agree that exascale supercomputers will raise new challenges, mostly because the trend in exascale compute-node hardware is toward heterogeneity and scalability: Compute nodes of future systems will have a combination of regular CPUs and accelerators (typically GPUs), along with a diversity of GPU architectures.

Meeting the needs of complex parallel applications and the requirements of exascale architectures raises numerous challenges which are still left unaddressed.
As a result, several parts of the software stack must evolve to better support these architectures. More importantly, the links between these parts must be strengthened to form a coherent, tightly integrated software suite.

Our project aims at consolidating the exascale software ecosystem by providing a coherent, exascale-ready software stack featuring breakthrough research advances enabled by multidisciplinary collaborations between researchers.

The main scientific challenges we intend to address are:

  • productivity,
  • performance portability,
  • heterogeneity,
  • scalability and resilience,
  • performance and energy efficiency.

AVALON is coordinating the WP1 and participates to WP1 and WP2

Project Information

  • URL: Not available yet
  • Starting date: 2023
  • End date: 2028
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Taranis : Model, Deploy, Orchestrate, and Optimize Cloud

A PEPR Cloud project

New infrastructures, such as Edge Computing or the Cloud-Edge-IoT computing continuum, make cloud issues more complex as they add new challenges related to resource diversity and heterogeneity (from small sensor to data center/HPC, from low power network to core networks), geographical distribution, as well as increased dynamicity and security needs, all under energy consumption and regulatory constraints.

In order to efficiently exploit new infrastructures, we propose a strategy based on a significant abstraction of the application structure description to further automate application and infrastructure management. Thus, it will be possible to globally optimize the resources used with respect to multi-criteria objectives (price, deadline, performance, energy, etc.) on both the user side (applications) and the provider side (infrastructures). This abstraction also includes the challenges related to the abstraction of application reconfiguration and to automatically adapt the use of resources.

The Taranis project addresses these issues through four scientific work packages, each focusing on a phase of the application lifecycle: application and infrastructure description models, deployment and reconfiguration, orchestration, and optimization.

The first work package “Modeling” addresses the complexity of cloud-edge application and infrastructure models: formal verification and optimization of these models, multi-layer variability, the relationship between model expressiveness and efficient solution computation, lock-ins of proprietary models, and heterogeneity of cloud application and infrastructure modeling languages.

The second work package “Deployment and Reconfiguration” studies deployment and reconfiguration related issues to reduce management complexity and increase support for provisioning and configuration languages, while improving operations certification and increasing operations concurrency. The workpackage also aims to reduce the complexity of the bootstrapping problem on geo-distributed and heterogeneous resources.

The third work package “Orchestration of services and resources” aims at extending the orchestrators for the Cloud-Edge-IoT continuum, while making them more autonomous with respect to dynamic, functional and/or non-functional needs, in particular with respect to the network partitioning problem specific to Cloud-Edge-IoT infrastructures.

Finally, the fourth work package “Optimization” aims to revisit the optimization problems associated with the use of Cloud-Edge-IoT infrastructures and the execution of an application when a large number of decision variables need to be considered jointly. It also aims to make optimization techniques aware of the Cloud-Edge-IoT continuum, the heterogeneous distributed platforms and the wide range of application configurations involved.

AVALON is coordinating the project and participated to the first two workpackages.

Project Information

  • URL: Not available yet
  • Starting date: 2023, September 1st
  • End date: 2030, August 31th
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SkyData

ANR-22-CE25-0008-01

Logo SkyData

Summary

A fundamental characteristic of our era is the deluge of Data. Since Grid environments, data management in distributed environments is a quite common practice and Cloud systems provide many solutions to store data. A data manager can be defined through its functionalities that can be understood as services, including security, replication strategy, green data transfer, synchronization, data migration, etc. Many ways to design those services exist and each data manager encompasses its own point of view to compose them. Usually, this point of view is centered on applications rather than data, even when an autonomic solution is provided.

The SkyData project aims at breaking the existing rules and the way the data management is in place nowadays. We propose a new paradigm without any centralized control nor middleware. Imagine a world where the data are controlled by themselves! It is a real challenge to provide an autonomic behavior for the data. In this project, we will endow data with autonomous behaviors and thus create a new entity, so-called Self-Managed Data (or SkyData). We plan to develop a distributed and autonomous environment where the data are regulated by themselves. This change of paradigm represents a huge and truly innovative challenge that can be split into three key challenges: the first one consists in a strong theoretical study on autonomic computing; the second one aims at developing the algorithmic support of the concepts; and the third one is the genesis of a prototype with this new generation of data and a significant use case. This latter will show how to use a SkyData environment to create an autonomous data-management system which produces a reduced carbon footprint.

Project Information

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Inria-Illinois-ANL-BSC-JSC-Riken/AICS Joint Laboratory on Extreme Scale Computing

In June 2014, The University of Illinois at Urbana-Champaign, Inria, the French national computer science institute, Argonne National Laboratory, Barcelona Supercomputing Center, Jülich Supercomputing Centre and the Riken Advanced Institute for Computational Science formed the Joint Laboratory for Extreme Scale Computing, a follow-up of the Inria-Illinois Joint Laboratory for Petascale Computing.

Research areas include:

  • Scientific applications (big compute and big data) that are the drivers of the research in the other topics of the joint-laboratory.
  • Modeling and optimizing numerical libraries, which are at the heart of many scientific applications.
  • Novel programming models and runtime systems, which allow scientific applications to be updated or reimagined to take full advantage of extreme-scale supercomputers.
  • Resilience and Fault-tolerance research, which reduces the negative impact when processors, disk drives, or memory fail in supercomputers that have tens or hundreds of thousands of those components.
  • I/O and visualization, which are important part of parallel execution for numerical silulations and data analytics.
  • HPC Clouds, that may execute a portion of the HPC workload in the near future.

More on the lab website

Start Date: 2014

Avalon Members: T. Gautier, L. Lefevre, C. Perez