University of Leeds Calder HPC first week (21 Oct): over 156,000 jobs, 90.3% average GPU utilisation on NVIDIA H200 NVL nodes and 82.2% peak utilisation, while proprietary applications and Slurm tuning are still catching up

What happened

The University of Leeds research computing team reports that in Calder's first seven days of service, researchers submitted over 156,000 jobs across a range of disciplines; GPU utilisation averaged 90.3% over the week and thousands of CPU jobs drove peak utilisation to 82.2%. Two researchers describe early use: a 3D scene-understanding group submitted over 2,700 CPU and 500 GPU jobs and said the H200 GPUs' large memory let them run big 3D models on whole scenes, and an Earth-sciences postdoc said the H200 NVL GPUs considerably sped up training of physics-informed neural networks. The team says the familiar setup carried over from the existing Aire cluster, but several applications, particularly proprietary software, are not yet available on Calder, users depending on them are asked to stay on Aire, and the team is still refining Slurm for growing and diverse workloads. The 9 October launch post says Calder was procured through an academic-led process approved by the Research IT Steering Group (MTI with Dell hardware, support from Cambridge Research Computing), with security checks and user testing before launch.

Why it matters

A rare early operating metric for a new university AI and HPC cluster. It shows demand for GPU capacity can saturate a new system within a week, and that software availability and scheduler tuning lag hardware, useful benchmarks for U.S. research computing centres planning launches and capacity.

Implementation considerations

Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.

Publication history

1. 2026-10-25Research Universities · Issue 474 resources