Keren Censor-Hillel, Tomer Even, Virginia Vassilevska Williams
{"title":"Faster Cycle Detection in the Congested Clique","authors":"Keren Censor-Hillel, Tomer Even, Virginia Vassilevska Williams","doi":"arxiv-2408.15132","DOIUrl":null,"url":null,"abstract":"We provide a fast distributed algorithm for detecting $h$-cycles in the\n\\textsf{Congested Clique} model, whose running time decreases as the number of\n$h$-cycles in the graph increases. In undirected graphs, constant-round\nalgorithms are known for cycles of even length. Our algorithm greatly improves\nupon the state of the art for odd values of $h$. Moreover, our running time\napplies also to directed graphs, in which case the improvement is for all\nvalues of $h$. Further, our techniques allow us to obtain a triangle detection\nalgorithm in the quantum variant of this model, which is faster than prior\nwork. A key technical contribution we develop to obtain our fast cycle detection\nalgorithm is a new algorithm for computing the product of many pairs of small\nmatrices in parallel, which may be of independent interest.","PeriodicalId":501422,"journal":{"name":"arXiv - CS - Distributed, Parallel, and Cluster Computing","volume":"50 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Distributed, Parallel, and Cluster Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.15132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We provide a fast distributed algorithm for detecting $h$-cycles in the
\textsf{Congested Clique} model, whose running time decreases as the number of
$h$-cycles in the graph increases. In undirected graphs, constant-round
algorithms are known for cycles of even length. Our algorithm greatly improves
upon the state of the art for odd values of $h$. Moreover, our running time
applies also to directed graphs, in which case the improvement is for all
values of $h$. Further, our techniques allow us to obtain a triangle detection
algorithm in the quantum variant of this model, which is faster than prior
work. A key technical contribution we develop to obtain our fast cycle detection
algorithm is a new algorithm for computing the product of many pairs of small
matrices in parallel, which may be of independent interest.