Fast n-point Correlation Function Approximation with Recursive Convolution for Scalar Fields

Xiang Zhang, Ce Yu
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引用次数: 6

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.
标量场的递归卷积快速n点相关函数逼近
在天体物理学中,n点相关函数(n-PCF)是一种重要的计算和分析工具,但其算法复杂性一直是一个突出的问题。本文将提出两种易于并行化的算法来高效地计算n-PCF问题。该算法基于标量场递归卷积(RCSF)的定义,并且可以使用文献中的各种快速傅里叶变换(FFT)算法进行计算。与传统的处理该问题的方法相比,我们的方法是最有效的,因为它可以在不到1分钟的时间内获得10亿个大点集的结果。此外,该算法本质上适用于并行计算环境,如计算机集群、多cpu /GPU超级计算机、MapReduce等。更好的计算环境可以处理更好的精度和时间要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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