{"title":"Scalability analysis of parallel systems with multiple components of work","authors":"E. Tambouris, P. V. Santen","doi":"10.1109/EMPDP.2000.823410","DOIUrl":null,"url":null,"abstract":"The generic fixed-value efficiency (FVE) method is proposed in order to study the scalability of parallel algorithms with multiple components of work. The generic FVE method is based on the isoefficiency method. Unlike isoefficiency, however, this method may be applied to parallel algorithm-machine combinations (parallel systems) where the relationship between the total work and its components is not predetermined by the decomposition method or by any other factor. The objective of the method is to derive the relationships between the total work and its components in order for the efficiency of the parallel system to be preserved. The use of the method is demonstrated by analysing the impact of the sparsity of the input data on the scalability of a static state estimator for power systems.","PeriodicalId":128020,"journal":{"name":"Proceedings 8th Euromicro Workshop on Parallel and Distributed Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 8th Euromicro Workshop on Parallel and Distributed Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EMPDP.2000.823410","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
The generic fixed-value efficiency (FVE) method is proposed in order to study the scalability of parallel algorithms with multiple components of work. The generic FVE method is based on the isoefficiency method. Unlike isoefficiency, however, this method may be applied to parallel algorithm-machine combinations (parallel systems) where the relationship between the total work and its components is not predetermined by the decomposition method or by any other factor. The objective of the method is to derive the relationships between the total work and its components in order for the efficiency of the parallel system to be preserved. The use of the method is demonstrated by analysing the impact of the sparsity of the input data on the scalability of a static state estimator for power systems.
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