PMO OpenIR
Parallel implementation of w-projection wide-field imaging
Lao, Baoqiang1; An, Tao1; Yu, Ang2; Zhang, Wenhui2,3; Wang, Junyi2; Guo, Quan1; Guo, Shaoguang1; Wu, Xiaocong1
2019-05-15
Source PublicationSCIENCE BULLETIN
ISSN2095-9273
Volume64Issue:9Pages:586-594
Corresponding AuthorAn, Tao(antao@shao.ac.cn)
Abstractw-Projection is a wide-field imaging technique that is widely used in radio synthesis arrays. Processing the wide-field big data generated by the future Square Kilometre Array (SKA) will require significant updates to current methods to significantly reduce the time consumed on data processing. Data loading and gridding are found to be two major time-consuming tasks in w-projection. In this paper, we investigate two parallel methods of accelerating w-projection processing on multiple nodes: the hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) method based on multicore Central Processing Units (CPUs) and the hybrid MPI and Compute Unified Device Architecture (CUDA) method based on Graphics Processing Units (GPUs). Both methods are successfully employed and operated in various computational environments, confirming their robustness. The experimental results show that the total runtime of both MPI + OpenMP and MPI + CUDA methods is significantly shorter than that of single-thread processing. MPI + CUDA generally shows faster performance when running on multiple nodes than MPI + OpenMP, especially on large numbers of nodes. The single-precision GPU-based processing yields faster computation than the double-precision processing; while the single- and doubleprecision CPU-based processing shows consistent computational performance. The gridding time remarkably increases when the support size of the convolution kernel is larger than 8 and the image size is larger than 2,048 pixels. The present research offers useful guidance for developing SKA imaging pipelines. (C) 2019 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.
KeywordRadio synthesis arrays Square kilometre array Wide field imaging Parallelization w-Projection
DOI10.1016/j.scib.2019.04.004
WOS KeywordTABLE DATA SYSTEM
Indexed BySCI
Language英语
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000472944600007
PublisherELSEVIER SCIENCE BV
Citation statistics
Document Type期刊论文
Identifierhttp://libir.pmo.ac.cn/handle/332002/27579
Collection中国科学院紫金山天文台
Corresponding AuthorAn, Tao
Affiliation1.Chinese Acad Sci, Shanghai Astron Observ, Key Lab Radio Astron, Shanghai 200030, Peoples R China
2.Guilin Univ Elect Technol, Guangxi Cooperat Innovat Ctr Cloud Comp & Big Dat, Guilin 541004, Peoples R China
3.Guilin Univ Elect Technol, Guangxi Coll & Univ Key Lab Cloud Comp & Complex, Guilin 541004, Peoples R China
Recommended Citation
GB/T 7714
Lao, Baoqiang,An, Tao,Yu, Ang,et al. Parallel implementation of w-projection wide-field imaging[J]. SCIENCE BULLETIN,2019,64(9):586-594.
APA Lao, Baoqiang.,An, Tao.,Yu, Ang.,Zhang, Wenhui.,Wang, Junyi.,...&Wu, Xiaocong.(2019).Parallel implementation of w-projection wide-field imaging.SCIENCE BULLETIN,64(9),586-594.
MLA Lao, Baoqiang,et al."Parallel implementation of w-projection wide-field imaging".SCIENCE BULLETIN 64.9(2019):586-594.
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