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- W2373455746 abstract "A GPU-based parallel star retrieval method is proposed to improve the efficiency of searching stars from star catalogue in computer simulation,especially when the Field of View(FOV) is large.By the novel algorithm,the stars in catalogue are classified and stored in different zones by using latitude and longitude zoned method firstly.Based on the easily accessible star catalogue,the star zones covered by the FOV can be computed exactly by constructing a spherical triangle around the FOV.As a result,the searching scope is reduced effectively.Finally,a CUDA computation platform is used to run the parallel process of star retrieving from those star zones on GPU.Experimental results show that,in comparison with CPU-oriented implementation,the proposed algorithm achieves up to decades times speedup,and the processing time is limited within a millisecond level in large FOV and wide star magnitude domain.It meets the requirement of real-time simulation." @default.
- W2373455746 created "2016-06-24" @default.
- W2373455746 creator A5062168363 @default.
- W2373455746 date "2012-01-01" @default.
- W2373455746 modified "2023-09-26" @default.
- W2373455746 title "Parallel Acceleration for a GPU-Based Star Catalogue Retrieval Algorithm" @default.
- W2373455746 hasPublicationYear "2012" @default.
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