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001052682 0247_ $$2datacite_doi$$a10.34734/FZJ-2026-01050
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001052682 1001_ $$0P:(DE-HGF)0$$aCiangottini, Diego$$b0$$eCorresponding author
001052682 1112_ $$aConference on Computing in High Energy and Nuclear Physics$$cKraków$$d2024-10-19 - 2024-10-25$$gCHEP 2024$$wPoland
001052682 245__ $$aUnlocking the compute continuum: Scaling out from cloud to HPC and HTC resources
001052682 260__ $$aLes Ulis$$bEDP Sciences$$c2025
001052682 300__ $$a8 p.
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001052682 4900_ $$aThe European physical journal / Web of Conferences
001052682 520__ $$aIn 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.
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001052682 536__ $$0G:(EU-Grant)101058386$$ainterTwin - An interdisciplinary Digital Twin Engine for science (101058386)$$c101058386$$fHORIZON-INFRA-2021-TECH-01$$x1
001052682 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001052682 7001_ $$0P:(DE-HGF)0$$aSpiga, Daniele$$b1
001052682 7001_ $$0P:(DE-Juel1)132191$$aMemon, Ahmed Shiraz$$b2$$ufzj
001052682 7001_ $$0P:(DE-HGF)0$$aManzi, Andrea$$b3
001052682 7001_ $$0P:(DE-HGF)0$$aFilipcic, Andrej$$b4
001052682 7001_ $$0P:(DE-HGF)0$$aTroja, Antonino$$b5
001052682 7001_ $$0P:(DE-HGF)0$$aFanzago, Federica$$b6
001052682 7001_ $$0P:(DE-HGF)0$$aBianchini, Giulio$$b7
001052682 7001_ $$0P:(DE-HGF)0$$aSgaravatto, Massimo$$b8
001052682 7001_ $$0P:(DE-HGF)0$$aPrica, Teo$$b9
001052682 7001_ $$0P:(DE-HGF)0$$aBoccali, Tommaso$$b10
001052682 7001_ $$0P:(DE-HGF)0$$aTedeschi, Tommaso$$b11
001052682 773__ $$0PERI:(DE-600)2595425-8$$a10.1051/epjconf/202533701296$$gVol. 337, p. 01296 -$$p01296$$v337$$x2100-014X$$y2025
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001052682 9141_ $$y2025
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