{"title":"A Parallel Approximation Algorithm for the Steiner Forest Problem","authors":"Laleh Ghalami, Daniel Grosu","doi":"10.1109/pdp55904.2022.00016","DOIUrl":null,"url":null,"abstract":"In the Steiner Forest problem, we are given an undirected graph with non-negative weights for edges, a set of pairs of vertices, called terminals, and the goal is to find the minimum cost subgraph that connects each of the terminal pairs together. There exist several sequential heuristic and approximation algorithms for the Steiner Forest problem. In practice, the primal-dual 2-approximation algorithm is one of the fastest and obtains solutions that are very close to the optimal solution. In this paper, we design a practical parallel approximation algorithm based on the primal-dual sequential algorithm. The parallel algorithm maintains the approximation guarantees of the sequential primal-dual algorithm and it is specifically designed for execution on multi-core computers. We implement and run the parallel algorithm on a multi-core system with a large number of cores and perform an extensive experimental performance analysis on randomly generated graphs. The results show that our proposed parallel approximation algorithm achieves a significant speedup with respect to the sequential primal-dual algorithm.","PeriodicalId":210759,"journal":{"name":"2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/pdp55904.2022.00016","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
In the Steiner Forest problem, we are given an undirected graph with non-negative weights for edges, a set of pairs of vertices, called terminals, and the goal is to find the minimum cost subgraph that connects each of the terminal pairs together. There exist several sequential heuristic and approximation algorithms for the Steiner Forest problem. In practice, the primal-dual 2-approximation algorithm is one of the fastest and obtains solutions that are very close to the optimal solution. In this paper, we design a practical parallel approximation algorithm based on the primal-dual sequential algorithm. The parallel algorithm maintains the approximation guarantees of the sequential primal-dual algorithm and it is specifically designed for execution on multi-core computers. We implement and run the parallel algorithm on a multi-core system with a large number of cores and perform an extensive experimental performance analysis on randomly generated graphs. The results show that our proposed parallel approximation algorithm achieves a significant speedup with respect to the sequential primal-dual algorithm.