| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01296 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/epjconf/202533701296 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701296
Unlocking the compute continuum: Scaling out from cloud to HPC and HTC resources
1 INFN Sezione di Perugia, Via A. Pascoli 23c, 06123 Perugia, Italy
2 EGI Foundation, Amsterdam, Netherlands
3 Jülich Supercomputing Centre, Forschungszentrum Jülich GmbH, Jülich, Germany
4 Jozef Stefan Institute (JSI), Jamova cesta 39, 1000 Ljubljana, Slovenija
5 Institute of Information Science (IZUM), Prešernova ulica 17, 2000 Maribor, Slovenia
6 INFN Sezione di Padova, via Marzolo 8, 35137 Padova, Italy
7 INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa, Italy
* e-mail: ciangottini@infn.it
Published online: 7 October 2025
In a geo-distributed computing infrastructure with heterogeneous resources (HPC and HTC and possibly cloud), a key to unlock an efficient and user-friendly access to the resources is being able to offload each specific task to the best suited location. One of the most critical problems involves the logistics of wide-area, multi-stage workflows that move back and forth between multiple resource providers. We envision a model where such a challenge can be addressed enabling a “transparent offloading” of containerized payloads using the Kubernetes API primitives creating a common cloud-native interface to access any number of external hardware machines and type of backends. Thus we created the interLink project, an open source extension to the concept of Virtual-Kubelet with a design that aims for a common abstraction over heterogeneous and distributed backends. interLink is developed by INFN in the context of interTwin, an EU funded project that aims to build a digital-twin platform (Digital Twin Engine) for sciences, and the ICSC National Research Center for High Performance Computing, Big Data and Quantum Computing in Italy. In this talk we first provide a comprehensive overview of the key features and the technical implementation. We showcase our major case studies, such as the scale-out of an analysis facility, and the distribution of ML training processes. We focus on the impacts of being able to seamlessly exploit world-class EuroHPC supercomputers with such a technology.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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