mlsanityData to 7 Oct 2026

JUWELS Booster -- A Supercomputer for Large-Scale AI Research

arXiv 2108.11976 ↗First posted 30 Jun 2021cs.DC cs.LGcited by 10

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Abstract (arXiv)

In this article, we present JUWELS Booster, a recently commissioned high-performance computing system at the J"ulich Supercomputing Center. With its system architecture, most importantly its large number of powerful Graphics Processing Units (GPUs) and its fast interconnect via InfiniBand, it is an ideal machine for large-scale Artificial Intelligence (AI) research and applications. We detail its system architecture, parallel, distributed model training, and benchmarks indicating its outstanding performance. We exemplify its potential for research application by presenting large-scale AI research highlights from various scientific fields that require such a facility.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 33 of its 71 references that are in the map. First posted on arXiv 30 Jun 2021.

Builds on

33 of 71 references.

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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 5; 2026: 2.

10 papers.

  1. 2025Lossy Neural Compression for Geospatial Analytics: A Reviewcited by 10
  2. 2024Parameter-efficient Bayesian Neural Networks for Uncertainty-aware Depth Estimationcited by 3
  3. 2024OneProt: Towards Multi-Modal Protein Foundation Modelscited by 2
  4. 2025Enhancing Monocular Depth Estimation with Multi-Source Auxiliary Taskscited by 2
  5. 20251LoRA: Summation Compression for Very Low-Rank Adaptationcited by 2
  6. 2025Contrastive Consolidation of Top-Down Modulations Achieves Sparsely Supervised Continual Learningcited by 1
  7. 2026Least but not Last: Fine-tuning Intermediate Principal Components for Better Performance-Forgetting Trade-Offscited by 1
  8. 2024Resource-Adaptive Successive Doubling for Hyperparameter Optimization with Large Datasets on High-Performance Computing Systemscited by 0
  9. 2025Evolutionary Architecture Search through Grammar-Based Sequence Alignmentcited by 0
  10. 2026Chain-of-Models Pre-Training: Rethinking Training Acceleration of Vision Foundation Modelscited by 0