mlsanityData to 14 Oct 2026

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

arXiv 2307.16885 ↗First posted 31 Jul 2023cs.DCcited by 12

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Abstract (arXiv)

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.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Jul 2023.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 8; 2026: 3.

12 papers.

  1. 2025High-Resolution Probabilistic Data-Driven Weather Modeling with a Stretched-Gridcited by 9
  2. 2024Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnectscited by 6
  3. 2025Designing Role Vectors to Improve LLM Inference Behaviourcited by 6
  4. 2025MoSE: Hierarchical Self-Distillation Enhances Early Layer Embeddingscited by 2
  5. 2025Learning High-dimensional Ionic Model Dynamics Using Fourier Neural Operatorscited by 2
  6. 2026Modalities, a PyTorch-native Framework For Large-scale LLM Training and Researchcited by 2
  7. 2025Bine Trees: Enhancing Collective Operations by Optimizing Communication Localitycited by 1
  8. 2025Swedish Whispers; Leveraging a Massive Speech Corpus for Swedish Speech Recognitioncited by 0
  9. 2025VOX-KRIKRI: Unifying Speech and Language through Continuous Fusioncited by 0
  10. 2025Multimodal Large Language Models for Low-Resource Languages: A Case Study for Basquecited by 0
  11. 2026Generative Nested Sampling of Atomistic Thermodynamic Landscapescited by 0
  12. 2026CodeGraph: Open-Taxonomy Knowledge Graph for Source Code with Wikidata Groundingcited by 0