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