{"title":"大规模扩散负载平衡的潜力","authors":"Matthias Lieber, Kerstin Gößner, W. Nagel","doi":"10.1145/2966884.2966887","DOIUrl":null,"url":null,"abstract":"Dynamic load balancing with diffusive methods is known to provide minimal load transfer and requires communication between neighbor nodes only. These are very attractive properties for highly parallel systems. We compare diffusive methods with state-of-the-art geometrical and graph-based partitioning methods on thousands of nodes. When load balancing overheads, i.e. repartitioning computation time and migration, have to be minimized, diffusive methods provide substantial benefits.","PeriodicalId":264069,"journal":{"name":"Proceedings of the 23rd European MPI Users' Group Meeting","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"The Potential of Diffusive Load Balancing at Large Scale\",\"authors\":\"Matthias Lieber, Kerstin Gößner, W. Nagel\",\"doi\":\"10.1145/2966884.2966887\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dynamic load balancing with diffusive methods is known to provide minimal load transfer and requires communication between neighbor nodes only. These are very attractive properties for highly parallel systems. We compare diffusive methods with state-of-the-art geometrical and graph-based partitioning methods on thousands of nodes. When load balancing overheads, i.e. repartitioning computation time and migration, have to be minimized, diffusive methods provide substantial benefits.\",\"PeriodicalId\":264069,\"journal\":{\"name\":\"Proceedings of the 23rd European MPI Users' Group Meeting\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 23rd European MPI Users' Group Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2966884.2966887\",\"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 of the 23rd European MPI Users' Group Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2966884.2966887","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Potential of Diffusive Load Balancing at Large Scale
Dynamic load balancing with diffusive methods is known to provide minimal load transfer and requires communication between neighbor nodes only. These are very attractive properties for highly parallel systems. We compare diffusive methods with state-of-the-art geometrical and graph-based partitioning methods on thousands of nodes. When load balancing overheads, i.e. repartitioning computation time and migration, have to be minimized, diffusive methods provide substantial benefits.
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