A Parallelized Binary Search Tree
A Parallelized Binary Search Tree
复制标题
并行二叉搜索树
DOI：
10.4172/2165-7866.1000103
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
B. Cooper
中科院分区：
文献类型：
--
作者：
Jian Feng;D. Naiman;B. Cooper
PTTRNFNDR是一种无监督的统计学习算法，可以检测DNA序列，蛋白质序列或任何可以分解为有限字母表的自然语言文本中的模式。PTTRNFNDR执行复杂的数学计算，当输入文本变大时，它的处理时间会增加。为了获得更好的速度性能，在程序的实现中采用了多种策略，包括二叉搜索树的并行操作。标准的二叉搜索树由于其动态插入和删除而不是线程安全的。在这里，我们调整了标准的二叉搜索树的并行操作，以提高性能的PTTRNFNDR算法。该方法可应用于其他软件平台，在满足多种条件时，通过二叉搜索树的并行运算，加快数据搜索速度。
PTTRNFNDR is an unsupervised statistical learning algorithm that detects patterns in DNA sequences, protein sequences, or any natural language texts that can be decomposed into letters of a finite alphabet. PTTRNFNDR performs complex mathematical computations, and its processing time increases when input texts become large. To achieve better speed performance, several strategies were applied in the implementation of the program, including parallel operations of binary search trees. A standard binary search tree is not thread-safe due to its dynamic insertions and deletions. Here, we adjusted the standard binary search tree for parallelized operations to achieve improved performance of the PTTRNFNDR algorithm. The method can be applied to other software platforms to quicken data searching through parallel operations of binary search trees when several conditions are met.