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低频射电脉冲星搜索的性能优化方法

Parallel optimization of the pulsar search pipeline on China SKA Regional Centre Prototype

摘要:随着平方公里阵列射电望远镜(SKA)等大科学装置的建设和运行,以及大数据和高性能计算创 新平台的提出,天文学与高性能计算之间的联系日趋紧密.天文学计算,特别是作为SKA的主要科学方 向之一的脉冲星搜索,具有数据量大、计算量多的特点.本文介绍了一种基于OpenMP多线程和多进程 技术来加速脉冲星搜索流程的方案,提出了一种解决负载不平衡问题的方法,并成功的将优化流程安装于 中国SKA区域中心原型机的x86和ARM计算节点.通过默奇森大视场阵列望远镜(MWA)的脉冲星观 测数据搜寻测试,与原始单线程方法相比,流程分别获得10.412.2和24.527.6倍的加速比.其中ARM平台比x86平台的计算快1.11.3倍,显示出其在SKA数据处理方面的巨大潜力.在中国SKA区域中心 原型机上部署的脉冲星优化搜索流程,近期将重点应用于MWA南天快速两米巡天(SMART)项目的低 频脉冲星搜寻,以满足包括引力波探测计时阵在内的多种科学需要。

英文摘要:The connection between astronomy and high performance computing is becoming stronger with the devel- opment of cutting-edge observing facilities such as the Square Kilometre Array (SKA) and the proposed innovative platform for big data and high performance computing. Astronomical computation is character- ized by huge data volume and massive parallelism, especially for pulsar search which is one of the leading scientific directions of the SKA. In this paper, we present an approach to accelerate the pulsar search pipeline based on OpenMP and multiprocessing techniques, propose a method to solve the load imbalance problem,and successfully has the pipeline installed on both x86 and ARM compute nodes on China SKA regional center prototype (CSRC-P). The performance evaluation from the tests on the Murchison Widefield Array (MWA) VCS observations shows that our optimization method works well on both x86 and ARM nodes, improving the relative speedup by a factor of 10.412.2 and 24.527.6, respectively, compared to the original single- thread approach. The ARM platform was found to be 1.11.3 times faster than the x86 platform in the tested cases, showing its great potential for SKA data processing. Recently, this optimized pulsar search pipeline deployed on CSRC-P will be especially used for low-frequency pulsar survey of the Southern-sky MWA Rapid Two-metre (SMART) program,for various scientific goals including pulsar timing arrays for gravitational wave detections.

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[V1] 2022-06-28 19:08:54 chinaXiv:202206.00186V1 下载全文
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