KMS National Astronomical Observatories, CAS
| HCGrid: a convolution-based gridding framework for radio astronomy in hybrid computing environments | |
| Wang, Hao1; Yu, Ce1; Zhang, Bo2,3; Xiao, Jian1; Luo, Qi1 | |
| 2021-02-01 | |
| Source Publication | MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
 |
| ISSN | 0035-8711 |
| Volume | 501Issue:2Pages:2734-2744 |
| Abstract | Gridding operation, which is to map non-uniform data samples on to a uniformly distributed grid, is one of the key steps in radio astronomical data reduction process. One of the main bottlenecks of gridding is the poor computing performance, and a typical solution for such performance issue is the implementation of multicore CPU platforms. Although such a method could usually achieve good results, in many cases, the performance of gridding is still restricted to an extent due to the limitations of CPU, since the main workload of gridding is a combination of a large number of single instruction, multidata stream operations, which is more suitable for GPU, rather than CPU implementations. To meet the challenge of massive data gridding for the modern large single-dish radio telescopes, e.g. the Five-hundred-meter Aperture Spherical radio Telescope, inspired by existing multicore CPU gridding algorithms such as Cygrid, here we present an easy-to-install, high-performance, and open-source convolutional gridding framework, HCGrid, in CPU-GPU heterogeneous platforms. It optimizes data search by employing multithreading on CPU, and accelerates the convolution process by utilizing massive parallelization of GPU. In order to make HCGrid a more adaptive solution, we also propose the strategies of thread organization and coarsening, as well as optimal parameter settings under various GPU architectures. A thorough analysis of computing time and performance gain with several GPU parallel optimization strategies show that it can lead to excellent performance in hybrid computing environments. |
| Keyword | methods: data analysis techniques: image processing software: public release |
| Funding Organization | National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC ; Chinese Academy of Sciences, NSFC ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; Open Project Program of the Key Laboratory of FAST ; NAOC ; NAOC ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC ; Chinese Academy of Sciences, NSFC ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; Open Project Program of the Key Laboratory of FAST ; NAOC ; NAOC ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC ; Chinese Academy of Sciences, NSFC ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; Open Project Program of the Key Laboratory of FAST ; NAOC ; NAOC ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC ; Chinese Academy of Sciences, NSFC ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; Open Project Program of the Key Laboratory of FAST ; NAOC ; NAOC ; Chinese Academy of Sciences ; Chinese Academy of Sciences |
| DOI | 10.1093/mnras/staa3800 |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC[U1731125] ; Chinese Academy of Sciences, NSFC[U1731243] ; Chinese Academy of Sciences, NSFC[11903056] ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; NAOC ; Chinese Academy of Sciences |
| Funding Organization | National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC ; Chinese Academy of Sciences, NSFC ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; Open Project Program of the Key Laboratory of FAST ; NAOC ; NAOC ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC ; Chinese Academy of Sciences, NSFC ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; Open Project Program of the Key Laboratory of FAST ; NAOC ; NAOC ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC ; Chinese Academy of Sciences, NSFC ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; Open Project Program of the Key Laboratory of FAST ; NAOC ; NAOC ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences, NSFC ; Chinese Academy of Sciences, NSFC ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Cultivation Project for FAST Scientific Payoff and Research Achievement of CAMS-CAS ; Open Project Program of the Key Laboratory of FAST ; Open Project Program of the Key Laboratory of FAST ; NAOC ; NAOC ; Chinese Academy of Sciences ; Chinese Academy of Sciences |
| WOS Research Area | Astronomy & Astrophysics |
| WOS Subject | Astronomy & Astrophysics |
| WOS ID | WOS:000608475600083 |
| Publisher | OXFORD UNIV PRESS |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.bao.ac.cn/handle/114a11/79861 |
| Collection | 中国科学院国家天文台 |
| Corresponding Author | Zhang, Bo; Xiao, Jian |
| Affiliation | 1.Tianjin Univ, Coll Intelligence & Comp, 135 Yaguan Rood,Haihe Educ Pk, Tianjin 300350, Peoples R China 2.Chinese Acad Sci, Natl Astron Observ, 20 Datun Rd, Beijing 100012, Peoples R China 3.Chinese Acad Sci, Natl Astron Observ, CAS Key Lab FAST, 20 Datun Rd, Beijing 100012, Peoples R China |
| Recommended Citation GB/T 7714 | Wang, Hao,Yu, Ce,Zhang, Bo,et al. HCGrid: a convolution-based gridding framework for radio astronomy in hybrid computing environments[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2021,501(2):2734-2744. |
| APA | Wang, Hao,Yu, Ce,Zhang, Bo,Xiao, Jian,&Luo, Qi.(2021).HCGrid: a convolution-based gridding framework for radio astronomy in hybrid computing environments.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,501(2),2734-2744. |
| MLA | Wang, Hao,et al."HCGrid: a convolution-based gridding framework for radio astronomy in hybrid computing environments".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 501.2(2021):2734-2744. |
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