Y. Ben-Asher, Aviad Cohen, A. Schuster, J. F. Sibeyn
{"title":"The impact of task-length parameters on the performance of the random load-balancing algorithm","authors":"Y. Ben-Asher, Aviad Cohen, A. Schuster, J. F. Sibeyn","doi":"10.1109/IPPS.1992.223067","DOIUrl":null,"url":null,"abstract":"Considers the problem of dynamic load balancing in an n processors parallel system. The authors focus on the algorithm which randomly assigns newly generated tasks to processors for execution. This process is modeled by randomly throwing weighted balls into n holes. For a given program A, the ball weights (task lengths) are chosen according to an unknown probability distribution D(A) with expectation mu , maximum M and minimum m. For any A, D(A) and a constant 0< in <or=0.5, they derive an upper bound on the number of processes which A needs to generate in order for the algorithm to achieve optimal load balancing with very high probability, so that the run-time is optimal up to a factor of (1+ in )/sup 2/. Using the relation derived, the programmer may control the load-balancing of his program by modifying the global parameters of the generated processes.<<ETX>>","PeriodicalId":340070,"journal":{"name":"Proceedings Sixth International Parallel Processing Symposium","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Sixth International Parallel Processing Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPPS.1992.223067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Considers the problem of dynamic load balancing in an n processors parallel system. The authors focus on the algorithm which randomly assigns newly generated tasks to processors for execution. This process is modeled by randomly throwing weighted balls into n holes. For a given program A, the ball weights (task lengths) are chosen according to an unknown probability distribution D(A) with expectation mu , maximum M and minimum m. For any A, D(A) and a constant 0< in >
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