论文标题
通往天文图像处理的门户：Vera C. rubinobservatory LSST科学管道在AWS上
A Gateway to Astronomical Image Processing: Vera C. RubinObservatory LSST Science Pipelines on AWS
论文作者
论文摘要
Vera C. Rubin天文台操作的时空的传统调查是一项为期10年的天文调查，原因是2022年的开始操作将每三个晚上拍摄一半的天空。 LSST每晚将产生约20TB的原始数据，该数据将几乎实时进行校准和分析。鉴于LSST数据的数量，传统的子集载荷过程范式的数据重新处理面临着重大挑战。我们在这里描述，这是迈出天文学科学门户的第一步，该步骤将使天文学家能够大规模分析图像和目录。在第一步中，我们着重于执行Amazon Web Services（AWS）上的Rubin LSST Science Pipelines，这是图像和目录处理算法的集合。我们描述了我们对在云中部署此类系统的性能，可扩展性和成本的最初印象。
The Legacy Survey of Space and Time, operated by the Vera C. Rubin Observatory, is a 10-year astronomical survey due to start operations in 2022 that will image half the sky every three nights. LSST will produce ~20TB of raw data per night which will be calibrated and analyzed in almost real time. Given the volume of LSST data, the traditional subset-download-process paradigm of data reprocessing faces significant challenges. We describe here, the first steps towards a gateway for astronomical science that would enable astronomers to analyze images and catalogs at scale. In this first step we focus on executing the Rubin LSST Science Pipelines, a collection of image and catalog processing algorithms, on Amazon Web Services (AWS). We describe our initial impressions on the performance, scalability and cost of deploying such a system in the cloud.
