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基于KDC树的高阶相关函数计算

High-order Correlation Function Calculation Based on KDC-tree
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摘要 高阶相关函数的计算复杂度随维度增加呈指数增长。为此,提出一种改进的高阶相关函数计算方法。在KDC树的数据结构基础上,设计剪枝搜索算法。针对三点相关函数给出该算法的具体实现,利用多线程并行技术对其进行加速,从而优化高阶相关函数的计算。实验结果验证了该方法的正确性和有效性。 The complexity of higher order correlation function increases exponentially with the growth of the dimension.An improved high-order correlation function calculation method is presented in this paper.A new pruning research algorithm based on the KDC-tree data structure is designed.The implementation of three points correlation function is given,and it is accelerated with parallel technology to optimize the calculation of high-order correlation function.Experimental results validate the correctness and efficiency of this method.
出处 《计算机工程》 CAS CSCD 2012年第12期26-28,共3页 Computer Engineering
基金 国家自然科学基金资助项目(10978016 11003027) 天津市科技支撑计划基金资助重点项目(09ZCKFGX00400 11ZCKFGX01000)
关键词 相关函数 KDC树结构 剪枝算法 并行计算 天文计算 高性能计算 correlation function KDC-tree structure pruning algorithm parallel calculation astronomical calculation high performance calculation
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