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.

翻译：现代射电干涉仪（如SKA先导望远镜）产生的数据量对成像流程提出了巨大的计算挑战。为满足高性能、可移植且可扩展软件的需求，我们推出了RICK 2.0（射电成像核心代码库）。本研究提出了一种创新实现方案，通过集成HeFFTe库实现分布式快速傅里叶变换，确保其在包括多核CPU与加速器在内的多种高性能计算架构上的可移植性。我们利用MeerKAT和LOFAR的实际观测数据验证了RICK的正确性与性能表现。结果表明，基于HeFFTe的实现方案具有显著的性能优势，尤其在GPU运行时表现突出，并能有效适应高像素分辨率与多频率平面的扩展需求。该新架构克服了前期研究（论文II、论文III）中识别的关键扩展瓶颈——此前因需传输完整网格数据导致通信开销最高占据96%的运行时间。新版RICK大幅降低了通信开销的影响，为SKA时代提供了可扩展且高效的成像解决方案。