在顶峰超级计算机上处理全尺寸平方公里阵列数据

Ruonan Wang, R. Tobar, M. Dolensky, Tao An, A. Wicenec, Chen Wu, F. Dulwich, N. Podhorszki, V. Anantharaj, E. Suchyta, B. Lao, S. Klasky
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引用次数: 8

摘要

本文提出了一种模拟和处理平方公里阵列(SKA)第一期全尺寸低频望远镜数据的工作流程。SKA项目将很快进入建设阶段,一旦建成,它将成为世界上最大的射电望远镜和世界上最大的数据发生器之一。作者使用Summit来模拟端到端SKA工作流程,模拟典型的6小时观测数据集,然后用成像管道处理该数据集。该工作流部署和运行在4,560个计算节点上,使用27,360个gpu生成2.6 PB的数据。这是射电天文数据第一次以这种规模进行处理。结果表明,该工作流能够处理SKA关键科学案例之一的再电离观测纪元。该分析还有助于揭示下一代射电望远镜和所需专用处理设施的关键设计因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Processing Full-Scale Square Kilometre Array Data on the Summit Supercomputer
This work presents a workflow for simulating and processing the full-scale low-frequency telescope data of the Square Kilometre Array (SKA) Phase 1. The SKA project will enter the construction phase soon, and once completed, it will be the world’s largest radio telescope and one of the world’s largest data generators. The authors used Summit to mimic an endto-end SKA workflow, simulating a dataset of a typical 6 hour observation and then processing that dataset with an imaging pipeline. This workflow was deployed and run on 4,560 compute nodes, and used 27,360 GPUs to generate 2.6 PB of data. This was the first time that radio astronomical data were processed at this scale. Results show that the workflow has the capability to process one of the key SKA science cases, an Epoch of Reionization observation. This analysis also helps reveal critical design factors for the next-generation radio telescopes and the required dedicated processing facilities.
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