二部图的GPU加速最大基数匹配算法
GPU accelerated maximum cardinality matching algorithms for bipartite graphs
摘要：
我们设计，实现和评估基于GPU的算法的最大基数匹配问题的二分图。这样的算法在计算机科学、科学计算、生物信息学和其它领域中具有多种应用。据我们所知，我们是第一个研究，重点是GPU实现的最大基数匹配算法。我们比较了所提出的算法与串行和多核实现从文献上的一个大的现实生活中的问题，在大多数情况下，我们的GPU加速算法之一被证明是比顺序和多核实现更快。
英文摘要：
We design, implement, and evaluate GPU-based algorithms for the maximum cardinality matching problem in bipartite graphs. Such algorithms have a variety of applications in computer science, scientific computing, bioinformatics, and other areas. To the best of our knowledge, ours is the first study which focuses on GPU implementation of the maximum cardinality matching algorithms. We compare the proposed algorithms with serial and multicore implementations from the literature on a large set of real-life problems where in majority of the cases one of our GPU-accelerated algorithms is demonstrated to be faster than both the sequential and multicore implementations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
