25–29 May 2026
Chulalongkorn University
Asia/Bangkok timezone

Expanding CloudVeneto: seamless integration of High Performance Computing resources for enhanced scientific collaboration

Not scheduled
18m
Chulalongkorn University

Chulalongkorn University

Poster Presentation Track 7 - Computing infrastructure and sustainability Poster

Speaker

Marco Verlato (INFN, Padova (IT))

Description

CloudVeneto is a private cloud targeted to scientific communities, based on OpenStack software, designed in 2013 to support INFN projects, initially mostly Nuclear Physics and HEP ones. During the last 12 years it evolved by integrating resources and use cases of several Departments of the University of Padova. It currently supports several scientific disciplines of different domains, but it is also used in other scenarios (e.g. to support teaching activities).
In 2025 CloudVeneto almost doubled its computing power capacity by integrating an “HPC Bubble”, i.e. a high-performance cluster designed for intensive computations, combining CPU and GPU nodes with low-latency interconnections, funded by the Italian National Recovery and Resilience Plan (NRRP). The Bubble is managed through a SLURM-based batch system, which enables flexible workload management. Given the features offered and the ease of use, several groups have decided to fund additional resources for the cluster. The Bubble is currently used by users involved in NRRP projects and in an opportunistic mode also by other users. Despite the HPC cluster being operated by a batch system outside the cloud environment, it shares with CloudVeneto a set of services as: resource provisioning and configuration; Ceph-based storage cluster; resource monitoring. Moreover, upon users’ request we can easily reconfigure some HPC nodes into Virtual Machines in the CloudVeneto environment, and viceversa.
In this paper we’ll describe in detail the solutions adopted to quickly put in production the HPC Bubble resources in an effective and integrated manner with the existing CloudVeneto infrastructure.

Authors

Alberto Crescente (INFN, Padova (IT)) Alberto Garfagnini (Universita e INFN, Padova (IT)) Antonino Troja (INFN, Padova (IT)) Federica Fanzago (INFN, Padova (IT)) Gianpietro Sella (Universita di Padova (IT)) Lisa Zangrando (INFN, Padova (IT)) Loris Lazzaro (Universita di Padova (IT)) Marco Verlato (INFN, Padova (IT)) Massimo Sgaravatto (INFN, Padova (IT)) Matteo Menguzzato (Universita di Padova (IT)) Paolo Andreetto (INFN, Padova (IT)) Rita Lenzo (INFN, Padova (IT)) Sergio Fantinel (INFN, Legnaro (IT)) Sergio Traldi (INFN, Padova (IT))

Presentation materials

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