astroCAMP: Sustainable Benchmarking for SKA-Scale Radio Imaging

This paper presents astroCAMP, a reproducible benchmarking and co-design framework for sustainable SKA-scale radio imaging. The Square Kilometre Array (SKA) will operate one of the world's largest continuous scientific data systems, requiring petascale imaging under strict power envelopes. Current radio-interferometric pipelines suffer from low hardware utilization, leading to high energy and operational costs. astroCAMP addresses this challenge by providing a unified metric suite, standardized datasets, and a multi-objective co-design formulation. The framework enables design-space exploration to derive Pareto-optimal operating regions. The authors evaluate WSClean+IDG on an AMD EPYC CPU and NVIDIA H100 GPU, revealing orchestration and synchronization bottlenecks. They call on the SKA community to define quantifiable fidelity thresholds to accelerate principled optimization. astroCAMP represents a significant step towards improving the efficiency and sustainability of SKA-scale radio imaging. This analysis is EU AI Act Art. 50 Compliant: The AI model provides a summary of a scientific paper on a benchmarking framework for radio imaging. The analysis is based solely on the provided text and aims to present the information accurately and objectively.

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