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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 PublicationMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
ISSN0035-8711
Volume501Issue:2Pages:2734-2744
AbstractGridding 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.
Keywordmethods: data analysis techniques: image processing software: public release
Funding OrganizationNational 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
DOI10.1093/mnras/staa3800
Language英语
Funding ProjectNational 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 OrganizationNational 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 AreaAstronomy & Astrophysics
WOS SubjectAstronomy & Astrophysics
WOS IDWOS:000608475600083
PublisherOXFORD UNIV PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/79861
Collection中国科学院国家天文台
Corresponding AuthorZhang, Bo; Xiao, Jian
Affiliation1.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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