文章基本信息

标题：A Parallelized Binary Search Tree
本地全文：下载
作者：Jian Feng ; Daniel Q. Naiman ; Bret Cooper 等
期刊名称：Information Technology & Software Engineering
电子版ISSN：2165-7866
出版年度：2011
卷号：1
期号：1
页码：103-103
DOI：10.4172/jitse.1000103
出版社：OMICS Group
摘要：PTTRNFNDR is an unsupervised statistical learning algorithm that detects patterns in DNA sequences, proteinsequences, or any natural language texts that can be decomposed into letters of a finite alphabet. PTTRNFNDRperforms complex mathematical computations, and its processing time increases when input texts become large. Toachieve better speed performance, several strategies were applied in the implementation of the program, includingparallel operations of binary search trees. A standard binary search tree is not thread-safe due to its dynamic insertionsand deletions. Here, we adjusted the standard binary search tree for parallelized operations to achieve improvedperformance of the PTTRNFNDR algorithm. The method can be applied to other software platforms to quicken datasearching through parallel operations of binary search trees when several conditions are met.
关键词：Computational speed; Data structure; Parallel processing.