astroCAMP: A Community Benchmark 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, sustaining petascale imaging under strict power envelopes. Yet current radio-interfe-rometric pipelines typically achieve only 4-14% of hardware peak because of memory and I/O bottlenecks, resulting in high energy, operational, and carbon costs. Progress is further constrained by the absence of standardised cross-layer metrics and survey-level fidelity tolerances for principled hardware-software co-design. We present astroCAMP, a reproducible benchmarking and co-design framework for SKA-scale imaging. astroCAMP contributes: (1) a unified metric suite spanning performance, utilisation, memory/data-movement behavior, sustainability, economics, and scientific fidelity; (2) standardised SKA-representative datasets, reference outputs, and benchmark configurations for reproducible cross-platform evaluation; (3) a multi-objective co-design formulation linking quality constraints to time-, energy-, carbon-, and cost-to-solution; and (4) a reproducible design-space exploration workflow to derive Pareto-optimal operating regions. We release datasets, scripts, benchmark results, and a reproducibility kit, and evaluate WS-Clean+IDG on an AMD EPYC 9334 CPU and an NVIDIA H100 GPU. The evaluation shows substantial end-to-end orchestration and synchronization bottlenecks despite efficient kernels in active phases, limited CPU strong scaling, and location-dependent carbon/cost efficiency under realistic grid and electricity-price assumptions. We further illustrate the use of astroCAMP for heterogeneous CPU-FPGA design-space exploration, and its potential to facilitate the identification of Pareto-optimal operating points for SKA-scale imaging deployments. Lastly, we call on the SKA community to define quantifiable fidelity metrics and thresholds to accelerate principled optimisation for SKA-scale imaging.