Abstract:
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.
Key words:
correlation function,
KDC-tree structure,
pruning algorithm,
parallel calculation,
astronomical calculation,
high performance calculation
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。
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
CLC Number:
CHEN Song, XU Ce, SUN Ji-Zhou, SUN Chao. High-order Correlation Function Calculation Based on KDC-tree[J]. Computer Engineering, 2012, 38(12): 26-28.
陈松, 于策, 孙济洲, 孙超. 基于KDC树的高阶相关函数计算[J]. 计算机工程, 2012, 38(12): 26-28.