LEONARDO: A Pan-European Pre-Exascale Supercomputer for HPC and AI applications

A new pre-exascale computer cluster has been designed to foster scientific progress and competitive innovation across European research systems, it is called LEONARDO. This paper describes thegeneral architecture of the system and focuses on the technologies adopted for its GPU-accelerated partition. High density processing elements, fast data movement capabilities and mature software stack collections allow the machine to run intensive workloads in a flexible and scalable way. Scientific applications from traditional High Performance Computing (HPC) as well as emerging Artificial Intelligence (AI) domains can benefit from this large apparatus in terms of time and energy to solution

LEONARDO: A Pan-European Pre-Exascale Supercomputer for HPC and AI Applications

A new pre-exascale computer cluster has been designed to foster scientific progress and competitive innovation across European research systems, it is called LEONARDO. This paper describes the general architecture of the system and focuses on the technologies adopted for its GPU-accelerated partition. High density processing elements, fast data movement capabilities and mature software stack collections allow the machine to run intensive workloads in a flexible and scalable way. Scientific applications from traditional High Performance Computing (HPC) as well as emerging Artificial Intelligence (AI) domains can benefit from this large apparatus in terms of time and energy to solution.Comment: 16 pages, 5 figures, 7 tables, to be published in Journal of Large Scale Research Facilitie

Crucial role of molecular curvature for the bend elastic and flexoelectric properties of liquid crystals: mesogenic dimers as a case study

International audienc

Fenix: Distributed e-Infrastructure Services for EBRAINS

The Human Brain Project (HBP) (https://humanbrainproject.eu/) is a large-scale flagship project funded by the European Commission with the goal of establishing a research infrastructure for brain science. This research infrastructure is currently being realised and will be called EBRAINS (https://ebrains.eu/). The wide ranging EBRAINS services for the brain research communities require diverse access, processing and storage capabilities. As a result, it will strongly rely on e-infrastructure services. The HBP led to the creation of Fenix (https://fenix-ri.eu/), a collaboration of five European supercomputing centres, who are providing a set of federated e-infrastructure services to EBRAINS. The Fenix architecture has been designed to uniquely address the need for a wide spectrum of services, from high performance computing (HPC) to on-demand cloud technologies to identity and access federation, for facilitating ease of access and usage of distributed e-infrastructure resources. In this article we describe the underlying concepts for an audience of computational science end-users and developers of domain-specific applications, workflows and platforms services. To exemplify the use of Fenix, we will discuss selected use cases demonstrating how brain researchers can use the offered infrastructure services and describe how access to these resources can be obtained.Funding for the work is received from the European Commission H2020 program under Specific Grant Agreement No. 800858 (ICEI). We would like to thank Timo Dickscheid (Forschungszentrum Jülich (FZJ), INM-1) for many discussions providing insight into the workflow for creating a brain atlas from brain imaging data.Peer Reviewed"Article signat per 27 autors/es: Sadaf Alam, Javier Bartolome, Sanzio Bassini, Michele Carpene, Mirko Cestari, Frederic Combeau, Sergi Girona, Stefano Gorini, Giuseppe Fiameni, Björn Hagemeier, Andreas Herten, Nikoleta Kiapidou, Wouter Klijn, Dorian Krause, Jacques-Charles Lafoucriere, Cerlane Leong, Thomas Leibovici, Thomas Lippert, Colin McMurtrie, Pavel Mezentsev, Anne Nahm, Boris Orth, Dirk Pleiter,Thomas Schulthess, Benedikt von St. Vieth, Debora Testi, Gilles Wiber"Postprint (published version

M100 ExaData: a data collection campaign on the CINECA’s Marconi100 Tier-0 supercomputer

Abstract Supercomputers are the most powerful computing machines available to society. They play a central role in economic, industrial, and societal development. While they are used by scientists, engineers, decision-makers, and data-analyst to computationally solve complex problems, supercomputers and their hosting datacenters are themselves complex power-hungry systems. Improving their efficiency, availability, and resiliency is vital and the subject of many research and engineering efforts. Still, a major roadblock hinders researchers: dearth of reliable data describing the behavior of production supercomputers. In this paper, we present the result of a ten-year-long project to design a monitoring framework (EXAMON) deployed at the Italian supercomputers at CINECA datacenter. We disclose the first holistic dataset of a tier-0 Top10 supercomputer. It includes the management, workload, facility, and infrastructure data of the Marconi100 supercomputer for two and half years of operation. The dataset (published via Zenodo) is the largest ever made public, with a size of 49.9TB before compression. We also provide open-source software modules to simplify access to the data and provide direct usage examples

Fenix: Distributed e-Infrastructure Services for EBRAINS

The Human Brain Project (HBP) (https://humanbrainproject.eu/) is a large-scale flagship project funded by the European Commission with the goal of establishing a research infrastructure for brain science. This research infrastructure is currently being realised and will be called EBRAINS (https://ebrains.eu/). The wide ranging EBRAINS services for the brain research communities require diverse access, processing and storage capabilities. As a result, it will strongly rely on e-infrastructure services. The HBP led to the creation of Fenix (https://fenix-ri.eu/), a collaboration of five European supercomputing centres, who are providing a set of federated e-infrastructure services to EBRAINS. The Fenix architecture has been designed to uniquely address the need for a wide spectrum of services, from high performance computing (HPC) to on-demand cloud technologies to identity and access federation, for facilitating ease of access and usage of distributed e-infrastructure resources. In this article we describe the underlying concepts for an audience of computational science end-users and developers of domain-specific applications, workflows and platforms services. To exemplify the use of Fenix, we will discuss selected use cases demonstrating how brain researchers can use the offered infrastructure services and describe how access to these resources can be obtained

Archival Data Repository Services to Enable HPC and Cloud Workflows in a Federated Research e-Infrastructure

Five European supercomputing centres, namely BSC (Spain), CEA (France), CINECA (Italy), CSCS (Switzerland), and JSC (Germany), agreed to align their high-end computing and storage services to facilitate the creation of the Fenix Research Infrastructure. In addition to the traditional extreme-scale computing and data services, Fenix provides a set of Cloud-type services as well as services needed for federation. In this paper, we describe the architecture of the Fenix infrastructure and how it can be used for representative workflows from the Human Brain Project (HBP). The concept of the Active Data Repository (ACD) is chosen to highlight demarcation between HPC and Cloud access models