{"title":"PCO Keynote","authors":"A. Pothen","doi":"10.1109/IPDPSW.2015.178","DOIUrl":null,"url":null,"abstract":"Computing a matching in a graph is one of \"the hardest simple problems\" in discrete mathematics and computer science. It is simple since most variants of matching can be solved in polynomial time, yet hard because the running times are high and the algorithms are complex. It is even more challenging to design parallel algorithms for matching, since many algorithms rely on searching for long paths in a graph, or implicitly communicate information along long paths, and thus have little concurrency. However, in the last fifteen years there has been much work in developing parallel matching algorithms via approximation: we do not find optimal matchings, but look for matchings that are guaranteed to be within a constant factor of being optimal. There has been a flurry of activity in designing and implementing such algorithms, and now we have efficient algorithms for computing matchings on multicore shared memory computers. This talk will survey this body of work in matching algorithms.","PeriodicalId":340697,"journal":{"name":"2015 IEEE International Parallel and Distributed Processing Symposium Workshop","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Parallel and Distributed Processing Symposium Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPSW.2015.178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

Computing a matching in a graph is one of "the hardest simple problems" in discrete mathematics and computer science. It is simple since most variants of matching can be solved in polynomial time, yet hard because the running times are high and the algorithms are complex. It is even more challenging to design parallel algorithms for matching, since many algorithms rely on searching for long paths in a graph, or implicitly communicate information along long paths, and thus have little concurrency. However, in the last fifteen years there has been much work in developing parallel matching algorithms via approximation: we do not find optimal matchings, but look for matchings that are guaranteed to be within a constant factor of being optimal. There has been a flurry of activity in designing and implementing such algorithms, and now we have efficient algorithms for computing matchings on multicore shared memory computers. This talk will survey this body of work in matching algorithms.
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计算图中的匹配是离散数学和计算机科学中“最难的简单问题”之一。它很简单,因为大多数匹配变量都可以在多项式时间内解决,但它很困难,因为运行时间长,算法复杂。设计用于匹配的并行算法更具挑战性,因为许多算法依赖于搜索图中的长路径,或者沿着长路径隐式地传递信息,因此几乎没有并发性。然而,在过去的15年里,通过近似开发并行匹配算法已经做了很多工作:我们没有找到最优匹配,而是寻找保证在一个恒定的最优因子范围内的匹配。在设计和实现这样的算法方面已经有了大量的活动,现在我们有了在多核共享内存计算机上计算匹配的有效算法。这个演讲将会调查匹配算法的工作。
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