{"title":"改进的寻找连接组件的并行算法","authors":"K. W. Chong, Tak-Wah Lam","doi":"10.1109/ICAPP.1995.472217","DOIUrl":null,"url":null,"abstract":"Finding the connected components of a graph is a basic computational problem. In recent years, there were several exciting results in breaking the log/sup 2/ n-time barrier to finding connected components on parallel machines using shared memory without concurrent-write capability. This paper further presents two new parallel algorithms both using less than log/sup 2/ n time. The merit of the first algorithm is that it uses only a sublinear number of processors, yet retains the time complexity of the fastest existing algorithm. The second algorithm is slightly slower but its work (i.e., the time-processor product) is closer to optimal than all previous algorithms using less than log/sup 2/ n time.<<ETX>>","PeriodicalId":448130,"journal":{"name":"Proceedings 1st International Conference on Algorithms and Architectures for Parallel Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Improved parallel algorithms for finding connected components\",\"authors\":\"K. W. Chong, Tak-Wah Lam\",\"doi\":\"10.1109/ICAPP.1995.472217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Finding the connected components of a graph is a basic computational problem. In recent years, there were several exciting results in breaking the log/sup 2/ n-time barrier to finding connected components on parallel machines using shared memory without concurrent-write capability. This paper further presents two new parallel algorithms both using less than log/sup 2/ n time. The merit of the first algorithm is that it uses only a sublinear number of processors, yet retains the time complexity of the fastest existing algorithm. The second algorithm is slightly slower but its work (i.e., the time-processor product) is closer to optimal than all previous algorithms using less than log/sup 2/ n time.<<ETX>>\",\"PeriodicalId\":448130,\"journal\":{\"name\":\"Proceedings 1st International Conference on Algorithms and Architectures for Parallel Processing\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 1st International Conference on Algorithms and Architectures for Parallel Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAPP.1995.472217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1st International Conference on Algorithms and Architectures for Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAPP.1995.472217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
寻找图的连通分量是一个基本的计算问题。近年来,有几个令人兴奋的结果打破了log/sup 2/ n-time的障碍,在使用共享内存而没有并发写能力的并行机器上找到连接的组件。本文进一步提出了两种新的并行算法,时间均小于log/sup 2/ n。第一种算法的优点是它只使用亚线性数量的处理器,但保留了现有最快算法的时间复杂度。第二种算法稍微慢一点,但它的工作(即时间处理器乘积)比之前的所有算法更接近于最优,所用时间小于log/sup 2/ n
Improved parallel algorithms for finding connected components
Finding the connected components of a graph is a basic computational problem. In recent years, there were several exciting results in breaking the log/sup 2/ n-time barrier to finding connected components on parallel machines using shared memory without concurrent-write capability. This paper further presents two new parallel algorithms both using less than log/sup 2/ n time. The merit of the first algorithm is that it uses only a sublinear number of processors, yet retains the time complexity of the fastest existing algorithm. The second algorithm is slightly slower but its work (i.e., the time-processor product) is closer to optimal than all previous algorithms using less than log/sup 2/ n time.<>