论文标题
降低脉冲星天文学的成本：使用nvidia gpus搜索二元脉冲星时节省时间和能量
Cutting the cost of pulsar astronomy: Saving time and energy when searching for binary pulsars using NVIDIA GPUs
论文作者
论文摘要
使用傅立叶域加速度搜索（FDA）方法搜索二进制脉冲星是一个计算昂贵的过程。下一代射电望远镜将不得不实时执行FDA，因为数据量太大而无法存储。 FDA是一种匹配的过滤方法，用于搜索具有近似线性加速度的二进制脉冲星的签名时间。在本文中，我们将探讨如何利用混合精液计算和NVIDIA GPU上的混合精液计算和动态频率缩放的组合，从而降低了类似SKA的FDA实现的能源成本。结合两种方法，我们设法节省了FDA的总体能源成本的58％，并在数值敏感性中牺牲（<3％）。
Using the Fourier Domain Acceleration Search (FDAS) method to search for binary pulsars is a computationally costly process. Next generation radio telescopes will have to perform FDAS in real time, as data volumes are too large to store. FDAS is a matched filtering approach for searching time-domain radio astronomy datasets for the signatures of binary pulsars with approximately linear acceleration. In this paper we will explore how we have reduced the energy cost of an SKA-like implementation of FDAS in AstroAccelerate, utilising a combination of mixed-precision computing and dynamic frequency scaling on NVIDIA GPUs. Combining the two approaches, we have managed to save 58% of the overall energy cost of FDAS with a (<3%) sacrifice in numerical sensitivity.
