期刊论文

中文

计算机应用研究

1001-3695

2014

31

10

2982-2985

10.3969/j.issn.1001-3695.2014.10.023

国家自然科学基金资助项目（61370095,61370098,61070057,90715029）：湖南省教育厅科学研究项目（13C074） 衡阳市科技局科技发展计划项目（2011KJ22） 湖南省教育科学“十二五”规划课题（XJK014CGD006）

本校为第一机构

针对多核CPU和GPU环境下图的深度优先搜索问题,提出多核CPU中实现并行DFS的新算法,通过有效利用内存带宽来提高性能,且当图增大时优势越明显。在此基础上提出一种混合方法,为DFS每一分支动态地选择最佳的实现:顺序执行;两种不同算法的多核执行;GPU执行。混合算法为每种大小的图提供相对更好的性能,且能避免高直径图上的最坏情况。通过比较多CPU和GPU系统,分析底层架构对DFS性能的影响。实验结果表明,一个高端single-socket GPU系统的DFS执行性能相当于一个高端4-socket CPU系统。

In order to solve the depth first search on multi-core CPU and GPU environment, this paper put forward a kind of parallel DFS algorithm on muhieore CPU . Through effective utilization of memory bandwidth to improve performance, and en- hanced its advantage as the size of the graph increased. Then the paper proposed a hybrid method which offered dynamical choices from a sequential execution, two different algorithms of multi-core execution, and a GPU execution, for each branch of DFS best implementation. Such hybrid method could provide the best performance for each size of the graph, and avoid...