DocumentCode :
3065130
Title :
Fast n-point Correlation Function Approximation with Recursive Convolution for Scalar Fields
Author :
Zhang, Xiang ; Yu, Ce
Author_Institution :
Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
fYear :
2011
fDate :
Nov. 29 2011-Dec. 1 2011
Firstpage :
634
Lastpage :
639
Abstract :
In astrophysics, n-point Correlation Function (n-PCF) is an important tool for computation and analysis, but its algorithmic complex has long been a notorious problem. In this paper we are going to propose two algorithms that are easy to be parallized to compute the n-PCF problem efficiently. The algorithms are based on the definition of recursive convolution for scalar fields (RCSF), and it can be computed using varous fast Fourier Transform (FFT) algorithms in literature. Compared to traditional ways of dealing with this problem, our method is most efficient, for that it can achieve results with point sets as large as 1 billion in less than 1 minute. Moreover, the algorithms are intrinsically appropriate to be used on parallel computing environments such as computer clusters, multi-CPU/GPU super-computers, MapReduce and etc. Better computing environments can deal with better accuracy and time requirements.
Keywords :
astronomical techniques; astronomy computing; convolution; correlation methods; fast Fourier transforms; function approximation; parallel processing; recursive functions; fast Fourier transform algorithm; fast n-point correlation function approximation; n-PCF problem; n-point correlation function; parallel computing environment; recursive convolution; scalar fields; Accuracy; Algorithm design and analysis; Clustering algorithms; Complexity theory; Convolution; Iterative methods; Quantization; astronomical computing; convolutional algorithms; correlation function approximation; fast Fourier Transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing Technology and Science (CloudCom), 2011 IEEE Third International Conference on
Conference_Location :
Athens
Print_ISBN :
978-1-4673-0090-2
Type :
conf
DOI :
10.1109/CloudCom.2011.98
Filename :
6133207
Link To Document :
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