Realizing the next generation of radio telescopes such as the Square Kilometre Array (SKA) requires both more efficient hardware and algorithms than today’s technology provides. The image-domain gridding (IDG) algorithm is a novel approach towards solving the most compute-intensive parts of creating sky images: gridding and degridding. It alleviates the performance bottlenecks of traditional AW-projection gridding by applying instrumental and environmental corrections in the image domain instead of in the Fourier domain. In this paper, we present a thorough performance analysis of this algorithm for an Intel Xeon CPU, Intel Xeon Phi, and GPUs from AMD and NVIDIA. We show that, by evaluating trigonometric functions in hardware, GPUs are both much faster and more energy efficient than a CPU or Xeon Phi. Furthermore, on GPUs, IDG is an order of magnitude faster and more energy efficient than traditional AW-projection. IDG on GPUs is the ideal candidate imaging technique for the SKA, as it meets the computational and energy constraints of the SKA Science Data Processor system.

实现诸如平方公里阵列（SKA）之类的下一代射电望远镜需要比当今技术更高效的硬件和算法。图像域网格化（IDG）算法是解决创建天空图像中计算量最大的部分的新方法：网格化和去网格化。通过在图像域而非傅立叶域中应用仪器和环境校正，可以减轻传统AW投影网格化的性能瓶颈。在本文中，我们对针对Intel Xeon CPU，Intel Xeon Phi和AMD和NVIDIA GPU的算法进行了全面的性能分析。我们显示出，通过评估硬件中的三角函数，GPU比CPU或至强融核（Xeon Phi）更快，更节能。此外，在GPU上，与传统的AW投影相比，IDG的速度更快且能源效率更高。GPU上的IDG是SKA的理想候选成像技术，因为它满足了SKA科学数据处理器系统的计算和能量要求。