Accelerating radio astronomy imaging with RICK: a step towards SKA-Mid and SKA-Low
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arXiv
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| Format: | Preprint |
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2026
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| author | Lacopo, Giovanni De Rubeis, Emanuele Gheller, Claudio Taffoni, Giuliano Tornatore, Luca |
| author_facet | Lacopo, Giovanni De Rubeis, Emanuele Gheller, Claudio Taffoni, Giuliano Tornatore, Luca |
| contents | The data volumes generated by modern radio interferometers, such as the SKA precursors, present significant computational challenges for imaging pipelines. Addressing the need for high-performance, portable, and scalable software, we present RICK 2.0 (Radio Imaging Code Kernels). This work introduces a novel implementation that leverages the HeFFTe library for distributed Fast Fourier Transforms, ensuring portability across diverse HPC architectures, including multi-core CPUs and accelerators. We validate RICK's correctness and performance against real observational data from both MeerKAT and LOFAR. Our results demonstrate that the HeFFTe-based implementation offers substantial performance advantages, particularly when running on GPUs, and scales effectively with large pixel resolutions and a high number of frequency planes. This new architecture overcomes the critical scaling limitations identified in previous work (Paper II, Paper III), where communication overheads consumed up to 96% of the runtime due to the necessity of communicating the entire grid. This new RICK version drastically reduces this communication impact, representing a scalable and efficient imaging solution ready for the SKA era. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_19714 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Accelerating radio astronomy imaging with RICK: a step towards SKA-Mid and SKA-Low Lacopo, Giovanni De Rubeis, Emanuele Gheller, Claudio Taffoni, Giuliano Tornatore, Luca Instrumentation and Methods for Astrophysics Distributed, Parallel, and Cluster Computing The data volumes generated by modern radio interferometers, such as the SKA precursors, present significant computational challenges for imaging pipelines. Addressing the need for high-performance, portable, and scalable software, we present RICK 2.0 (Radio Imaging Code Kernels). This work introduces a novel implementation that leverages the HeFFTe library for distributed Fast Fourier Transforms, ensuring portability across diverse HPC architectures, including multi-core CPUs and accelerators. We validate RICK's correctness and performance against real observational data from both MeerKAT and LOFAR. Our results demonstrate that the HeFFTe-based implementation offers substantial performance advantages, particularly when running on GPUs, and scales effectively with large pixel resolutions and a high number of frequency planes. This new architecture overcomes the critical scaling limitations identified in previous work (Paper II, Paper III), where communication overheads consumed up to 96% of the runtime due to the necessity of communicating the entire grid. This new RICK version drastically reduces this communication impact, representing a scalable and efficient imaging solution ready for the SKA era. |
| title | Accelerating radio astronomy imaging with RICK: a step towards SKA-Mid and SKA-Low |
| topic | Instrumentation and Methods for Astrophysics Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2601.19714 |